Data file compression

ABSTRACT

A computer implemented method of reducing data elements in a data file includes: receiving a data file including one or more primary data elements; storing the data file in a memory coupled to the processor; generating, from at least one of the one or more primary data elements, a plurality of supplemental data elements; determining whether any of the plurality of supplemental data elements and any of the primary data elements offset each other; and upon determining that at least one of the plurality of supplemental data elements and at least one of the primary data elements offset each other, deleting, from the data file, at least one of the offset supplemental data elements or primary data elements.

BACKGROUND

While costs associated with computers and memory storage products havebeen falling with technological improvements, available computingresources of organizations remain at a premium. For example, asbusinesses increasingly move towards electronic communications,electronic processing of business processes, and electronicallymonitoring these communications and business processes, memory usage andcomputing processing power needs also correspondingly increase. In manycases, computing centers tasked with implementing and maintaining theseelectronic communications and business processes are constrained byexisting or aging hardware and software resources, and budgetaryconcerns regarding the purchase, upgrade, or repair of the hardware andsoftware infrastructure components. This may be true for large or smallbusiness organizations. In an illustrative example, a large organizationmay have many clients engaging in large numbers of electronictransactions, the details of which may be stored in memory. In manycases, these electronic transactions for multiple clients may occurcontinually and/or concurrently. As such computing resources, such asmemory/storage, may be depleted and additional resources may need to beadded to the system. Additionally, the data stored may be communicatedbetween computing systems for processing. These communicationrequirements may result in slowed communications capability, ascommunication bandwidth on an organization's network may be a finite,limited resource. As such, a need has been recognized for improved datamanagement capabilities, in storage capacity and transmission bandwidthmanagement, while maintaining desired parameters/business value of theunderlying data.

For example, computer systems and networks are commonly used toelectronically trade securities and derivatives. Electronic tradinginvolves traders transmitting electronic data transaction requestmessages to an exchange computing system that includes one or morehardware match engines that match, or attempt to match, the datatransaction request messages. Once a trade event occurs, e.g., two ofthe transaction requests are matched, the result is that the marketparticipants involved in the match have positions which may be clearedby the exchange computing system. Market participants, e.g., traders orclearing firms, may be associated with large portfolios comprisinghundreds, thousand, or even millions of positions that eventually willbe cleared. A position may be defined as open interest in a futures oroptions contract after a trade event has occurred, e.g., the outstandingderivatives (e.g., futures or options) contracts or post-tradecommitments associated with a market participant. Each outstandingfutures or options contract for a market participant, e.g., a trader,accordingly contributes to the open interest associated with thattrader.

A market participant portfolio, which includes open interest/positions,is associated with a computing cost as well as a financial cost. From acomputing resources standpoint, the exchange computing system may storeall the post-trade positions associated with a trader, i.e., thetrader's portfolio, in a data file, which may be processed and managedby the exchange computing system, and which may then be transmitted overa network to other institutions, such as regulators, or banks, or anyother financial institution. Open positions may be represented as dataelements in the data file.

Many financial institutions that work with the exchange computing systemrequire traders to post capital requirements that are based on the openinterest associated with each trader. Thus, in addition to the computingcosts of maintaining, processing and transmitting large data files withmany data elements, open interest may also trigger capital requirements,which can burden traders and reduce the overall amount of trading thatcan be performed by the trader.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts a computer network system, according to some embodiments.

FIG. 2 depicts a general computer system, according to some embodiments.

FIGS. 3A to 3C depict various storage data structures, according to someembodiments.

FIG. 4 depicts a match engine module, according to some embodiments.

FIG. 5 depicts a block diagram of an exchange computing system includinga optimization system, according to some embodiments.

FIGS. 6A and 6B illustrate example exchange traded derivativeportfolios, according to some embodiments.

FIG. 7 depicts another block diagram of an exchange computing systemincluding a optimization system, according to some embodiments.

FIG. 8 depicts a block diagram of a system for reducing the size of aportfolio, according to some embodiments.

FIG. 9 illustrates an example flowchart for reducing data elements in adata file, according to some embodiments.

DETAILED DESCRIPTION I. Exchange Computing System

The disclosed embodiments may be implemented in association with a datatransaction processing system that processes data items or objects, suchas an exchange computing system. Customer or user devices (e.g., clientcomputers) may submit electronic data transaction request messages,e.g., inbound messages, to the data transaction processing system over adata communication network. The electronic data transaction requestmessages may include, for example, transaction matching parameters, suchas instructions and/or values, for processing the data transactionrequest messages within the data transaction processing system. Theinstructions may be to perform transactions, e.g., buy or sell aquantity of a product at a specified price. Products, e.g., financialinstruments, or order books representing the state of an electronicmarketplace for a product, may be represented as data objects within theexchange computing system. The instructions may also be conditional,e.g., buy or sell a quantity of a product at a given value if a tradefor the product is executed at some other reference value.

The data transaction processing system may include various specificallyconfigured matching processors that match, e.g., automatically,electronic data transaction request messages for the same one of thedata items or objects. The specifically configured matching processorsmay match, or attempt to match, electronic data transaction requestmessages based on multiple transaction matching parameters from thedifferent client computers. Input electronic data transaction requestmessages may be received from different client computers over a datacommunication network, and output electronic data transaction resultmessages may be transmitted to the client computers and may beindicative of results of the attempts to match incoming electronic datatransaction request messages. The specifically configured matchingprocessors may additionally generate information indicative of a stateof an environment (e.g., the state of the order book) based on theprocessing of the electronic data transaction request messages, andreport this information to data recipient computing systems via outboundmessages published via one or more data feeds that contain electronicdata transaction result messages. While the disclosed embodiments may bedescribed with respect to electronic data transaction request and resultmessages, it will be appreciated that the disclosed embodiments may beimplemented with respect to other technologies later developed, such asphotonic, e.g., light-based, messages.

For example, one exemplary environment where the disclosed embodimentsmay be desirable is in financial markets, and in particular, electronicfinancial exchanges, such as a futures exchange, such as the ChicagoMercantile Exchange Inc. (CME).

An exchange provides one or more markets for the purchase and sale ofvarious types of products including financial instruments such asstocks, bonds, futures contracts, options, currency, cash, and othersimilar instruments. Agricultural products and commodities are alsoexamples of products traded on such exchanges. A futures contract is aproduct that is a contract for the future delivery of another financialinstrument such as a quantity of grains, metals, oils, bonds, currency,or cash. Generally, each exchange establishes a specification for eachmarket provided thereby that defines at least the product traded in themarket, minimum quantities that must be traded, and minimum changes inprice (e.g., tick size). For some types of products (e.g., futures oroptions), the specification further defines a quantity of the underlyingproduct represented by one unit (or lot) of the product, and deliveryand expiration dates. As will be described, the exchange may furtherdefine the matching algorithm, or rules, by which incoming orders willbe matched/allocated to resting orders.

Generally, a market may involve market makers, such as marketparticipants who consistently provide bids and/or offers at specificprices in a manner typically conducive to balancing risk, and markettakers who may be willing to execute transactions at prevailing bids oroffers may be characterized by more aggressive actions so as to maintainrisk and/or exposure as a speculative investment strategy. From analternate perspective, a market maker may be considered a marketparticipant who places an order to sell at a price at which there is nopreviously or concurrently provided counter order. Similarly, a markettaker may be considered a market participant who places an order to buyat a price at which there is a previously or concurrently providedcounter order. A balanced and efficient market may involve both marketmakers and market takers, coexisting in a mutually beneficial basis. Themutual existence, when functioning properly, may facilitate liquidity inthe market such that a market may exist with “tight” bid-ask spreads(e.g., small difference between bid and ask prices) and a “deep” volumefrom many currently provided orders such that large quantity orders maybe executed without driving prices significantly higher or lower.

In many cases, market makers may place bids and asks on both sides of amarket, e.g., a bid for a contract and an ask for the same contract. Forexample, market makers may be incentivized to execute bid and ask tradeson both sides of a contract, or to place a bid request and an askrequest on the same financial instrument. As many of those tradesexecute, i.e., the market maker's bid and ask positions are matched(with other traders), a market maker's portfolio may include hundreds orthousands of post-trade positions that need to be cleared. An exchangecomputing system typically prevents such bids and asks from the samemarket participant from matching each other through self-matchprevention systems. For information and examples about self-matchprevention systems, see U.S. Patent Publication No. 2015/0026033, filedon Oct. 3, 2014, entitled “Efficient Self-Match Prevention In AnElectronic Match Engine”, assigned to the assignee of the presentapplication, the entirety of which is incorporated by reference hereinand relied upon.

A financial instrument trading system, such as a futures exchange, suchas the Chicago Mercantile Exchange Inc. (CME), provides a contractmarket where financial instruments, e.g., futures and options onfutures, are traded using electronic systems. “Futures” is a term usedto designate all contracts for the purchase or sale of financialinstruments or physical commodities for future delivery or cashsettlement on a commodity futures exchange. A futures contract is alegally binding agreement to buy or sell a commodity at a specifiedprice at a predetermined future time. An option contract is the right,but not the obligation, to sell or buy the underlying instrument (inthis case, a futures contract) at a specified price on or before acertain expiration date. An option contract offers an opportunity totake advantage of futures price moves without actually having a futuresposition. The commodity to be delivered in fulfillment of the contract,or alternatively the commodity for which the cash market price shalldetermine the final settlement price of the futures contract, is knownas the contract's underlying reference or “underlier.” The underlying orunderlier for an options contract is the corresponding futures contractthat is purchased or sold upon the exercise of the option.

The terms and conditions of each futures contract are standardized as tothe specification of the contract's underlying reference commodity, thequality of such commodity, quantity, delivery date, and means ofcontract settlement. Cash settlement is a method of settling a futurescontract whereby the parties effect final settlement when the contractexpires by paying/receiving the loss/gain related to the contract incash, rather than by effecting physical sale and purchase of theunderlying reference commodity at a price determined by the futurescontract, price. Options and futures may be based on more generalizedmarket indicators, such as stock indices, interest rates, futurescontracts and other derivatives.

An exchange may provide for a centralized “clearing house” through whichtrades made must be confirmed, matched, and settled each day untiloffset or delivered. The clearing house may be an adjunct to anexchange, and may be an operating division of an exchange, which isresponsible for settling trading accounts, clearing trades, collectingand maintaining performance bond funds, regulating delivery, andreporting trading data. One of the roles of the clearing house is tomitigate credit risk. Clearing is the procedure through which theclearing house becomes buyer to each seller of a futures contract, andseller to each buyer, also referred to as a novation, and assumesresponsibility for protecting buyers and sellers from financial loss dueto breach of contract, by assuring performance on each contract. Aclearing member is a firm qualified to clear trades through the clearinghouse.

An exchange computing system may operate under a central counterpartymodel, where the exchange acts as an intermediary between marketparticipants for the transaction of financial instruments. Inparticular, the exchange computing system novates itself into thetransactions between the market participants, i.e., splits a giventransaction between the parties into two separate transactions where theexchange computing system substitutes itself as the counterparty to eachof the parties for that part of the transaction, sometimes referred toas a novation. In this way, the exchange computing system acts as aguarantor and central counterparty and there is no need for the marketparticipants to disclose their identities to each other, or subjectthemselves to credit or other investigations by a potentialcounterparty. For example, the exchange computing system insulates onemarket participant from the default by another market participant.Market participants need only meet the requirements of the exchangecomputing system. Anonymity among the market participants encourages amore liquid market environment as there are lower barriers toparticipation. The exchange computing system can accordingly offerbenefits such as centralized and anonymous matching and clearing.

A match engine within a financial instrument trading system may comprisea transaction processing system that processes a high volume, e.g.,millions, of messages or orders in one day. The messages are typicallysubmitted from market participant computers. Exchange match enginesystems may be subject to variable messaging loads due to variablemarket messaging activity. Performance of a match engine depends to acertain extent on the magnitude of the messaging load and the workneeded to process that message at any given time. An exchange matchengine may process large numbers of messages during times of high volumemessaging activity. With limited processing capacity, high messagingvolumes may increase the response time or latency experienced by marketparticipants.

Electronic messages such as incoming messages from market participants,i.e., “outright” messages, e.g., trade order messages, etc., are sentfrom client devices associated with market participants, or theirrepresentatives, to an electronic trading or market system.

II. Electronic Trading

Electronic trading of financial instruments, such as futures contracts,is conducted by market participants sending orders, such as to buy orsell one or more futures contracts, in electronic form to the exchange.These electronically submitted orders to buy and sell are then matched,if possible, by the exchange, i.e., by the exchange's matching engine,to execute a trade. Outstanding (unmatched, wholly unsatisfied/unfilledor partially satisfied/filled) orders are maintained in one or more datastructures or databases referred to as “order books,” such orders beingreferred to as “resting,” and made visible, i.e., their availability fortrading is advertised, to the market participants through electronicnotifications/broadcasts, referred to as market data feeds. An orderbook is typically maintained for each product, e.g., instrument, tradedon the electronic trading system and generally defines or otherwiserepresents the state of the market for that product, i.e., the currentprices at which the market participants are willing buy or sell thatproduct. As such, as used herein, an order book for a product may alsobe referred to as a market for that product.

Upon receipt of an incoming order to trade in a particular financialinstrument, whether for a single-component financial instrument, e.g., asingle futures contract, or for a multiple-component financialinstrument, e.g., a combination contract such as a spread contract, amatch engine, as described herein, will attempt to identify a previouslyreceived but unsatisfied order counter thereto, i.e., for the oppositetransaction (buy or sell) in the same financial instrument at the sameor better price (but not necessarily for the same quantity unless, forexample, either order specifies a condition that it must be entirelyfilled or not at all).

Previously received but unsatisfied orders, i.e., orders which eitherdid not match with a counter order when they were received or theirquantity was only partially satisfied, referred to as a partial fill,are maintained by the electronic trading system in an order bookdatabase/data structure to await the subsequent arrival of matchingorders or the occurrence of other conditions which may cause the orderto be modified or otherwise removed from the order book.

If the match engine identifies one or more suitable previously receivedbut unsatisfied counter orders, they, and the incoming order, arematched to execute a trade there between to at least partially satisfythe quantities of one or both the incoming order or the identifiedorders. If there remains any residual unsatisfied quantity of theidentified one or more orders, those orders are left on the order bookwith their remaining quantity to await a subsequent suitable counterorder, i.e., to rest. If the match engine does not identify a suitablepreviously received but unsatisfied counter order, or the one or moreidentified suitable previously received but unsatisfied counter ordersare for a lesser quantity than the incoming order, the incoming order isplaced on the order book, referred to as “resting”, with original orremaining unsatisfied quantity, to await a subsequently receivedsuitable order counter thereto. The match engine then generates matchevent data reflecting the result of this matching process. Othercomponents of the electronic trading system, as will be described, thengenerate the respective order acknowledgment and market data messagesand transmit those messages to the market participants.

Matching, which is a function typically performed by the exchange, is aprocess, for a given order which specifies a desire to buy or sell aquantity of a particular instrument at a particular price, ofseeking/identifying one or more wholly or partially, with respect toquantity, satisfying counter orders thereto, e.g., a sell counter to anorder to buy, or vice versa, for the same instrument at the same, orsometimes better, price (but not necessarily the same quantity), whichare then paired for execution to complete a trade between the respectivemarket participants (via the exchange) and at least partially satisfythe desired quantity of one or both of the order and/or the counterorder, with any residual unsatisfied quantity left to await anothersuitable counter order, referred to as “resting.” A match event mayoccur, for example, when an aggressing order matches with a restingorder. In one embodiment, two orders match because one order includesinstructions for or specifies buying a quantity of a particularinstrument at a particular price, and the other order includesinstructions for or specifies selling a (different or same) quantity ofthe instrument at a same or better price. It should be appreciated thatperforming an instruction associated with a message may includeattempting to perform the instruction. Whether or not an exchangecomputing system is able to successfully perform an instruction maydepend on the state of the electronic marketplace.

While the disclosed embodiments will be described with respect to aproduct by product or market by market implementation, e.g. implementedfor each market/order book, it will be appreciated that the disclosedembodiments may be implemented so as to apply across markets formultiple products traded on one or more electronic trading systems, suchas by monitoring an aggregate, correlated or other derivation of therelevant indicative parameters as described herein.

While the disclosed embodiments may be discussed in relation to futuresand/or options on futures trading, it should be appreciated that thedisclosed embodiments may be applicable to any equity, fixed incomesecurity, currency, commodity, options or futures trading system ormarket now available or later developed. It may be appreciated that atrading environment, such as a futures exchange as described herein,implements one or more economic markets where rights and obligations maybe traded. As such, a trading environment may be characterized by a needto maintain market integrity, transparency, predictability,fair/equitable access and participant expectations with respect thereto.In addition, it may be appreciated that electronic trading systemsfurther impose additional expectations and demands by marketparticipants as to transaction processing speed, latency, capacity andresponse time, while creating additional complexities relating thereto.Accordingly, as will be described, the disclosed embodiments may furtherinclude functionality to ensure that the expectations of marketparticipants are met, e.g., that transactional integrity and predictablesystem responses are maintained.

Financial instrument trading systems allow traders to submit orders andreceive confirmations, market data, and other information electronicallyvia electronic messages exchanged using a network. Electronic tradingsystems ideally attempt to offer a more efficient, fair and balancedmarket where market prices reflect a true consensus of the value oftraded products among the market participants, where the intentional orunintentional influence of any one market participant is minimized ifnot eliminated, and where unfair or inequitable advantages with respectto information access are minimized if not eliminated.

Electronic marketplaces attempt to achieve these goals by usingelectronic messages to communicate actions and related data of theelectronic marketplace between market participants, clearing firms,clearing houses, and other parties. The messages can be received usingan electronic trading system, wherein an action or transactionassociated with the messages may be executed. For example, the messagemay contain information relating to an order to buy or sell a product ina particular electronic marketplace, and the action associated with themessage may indicate that the order is to be placed in the electronicmarketplace such that other orders which were previously placed maypotentially be matched to the order of the received message. Thus theelectronic marketplace may conduct market activities through electronicsystems.

As may be perceived/experienced by the market participants from outsidethe Exchange or electronic trading system operated thereby, thefollowing sequence describes how, at least in part, information may bepropagated in such a system and how orders may be processed: (1) Anopportunity is created at a matching engine of the Exchange, such as byplacing a recently received but unmatched order on the order book torest; (2) The matching engine creates an update reflecting theopportunity and sends it to a feed engine; (3) The feed enginemulticasts it to all of the market participants to advertise theopportunity to trade; (4) The market participants evaluate theopportunity and each, upon completion of their evaluation, may or maynot choose to respond with an order responsive to the resting order,i.e. counter to the resting order; (5) The Exchange gateway receives anycounter orders generated by the market participants, sends confirmationof receipt back directly to each submitting market participant, andforwards the received orders to the matching engine; and (6) Thematching engine evaluates the received orders and matches the firstarriving order against the resting opportunity and a trade is executed.

III. Electronic Data Transaction Request/Result Messages and Market DataFeeds

As used herein, a financial message, or an electronic message, refersboth to messages communicated by market participants to an electronictrading or market system and vice versa. The messages may becommunicated using packeting or other techniques operable to communicateinformation between systems and system components. Some messages may beassociated with actions to be taken in the electronic trading or marketsystem. In particular, in one embodiment, upon receipt of a request, atoken is allocated and included in a TCP shallow acknowledgmenttransmission sent back to the participant acknowledging receipt of therequest. It should be appreciated that while this shallow acknowledgmentis, in some sense, a response to the request, it does not confirm theprocessing of an order included in the request. The participant, i.e.,their device, then sends back a TCP acknowledgment which acknowledgesreceipt of the shallow acknowledgment and token.

Financial messages communicated to the electronic trading system, alsoreferred to as “inbound” messages, may include associated actions thatcharacterize the messages, such as trader orders, order modifications,order cancellations and the like, as well as other message types.Inbound messages may be sent from client devices associated with marketparticipants, or their representatives, e.g., trade order messages,etc., to an electronic trading or market system. For example, a marketparticipant may submit an electronic message to the electronic tradingsystem that includes an associated specific action to be undertaken bythe electronic trading system, such as entering a new trade order intothe market or modifying an existing order in the market. In oneembodiment, if a participant wishes to modify a previously sent request,e.g., a prior order which has not yet been processed or traded, they maysend a request message comprising a request to modify the prior request.In one exemplary embodiment, the incoming request itself, e.g., theinbound order entry, may be referred to as an iLink message. iLink is abidirectional communications/message protocol/message format implementedby the Chicago Mercantile Exchange Inc.

Financial messages communicated from the electronic trading system,referred to as “outbound” messages, may include messages responsive toinbound messages, such as confirmation messages, or other messages suchas market update messages, quote messages, and the like. Outboundmessages, or electronic data transaction result messages, may bedisseminated via data feeds.

Financial messages may further be categorized as having or reflecting animpact on a market or electronic marketplace, also referred to as an“order book” or “book,” for a traded product, such as a prevailing pricetherefore, number of resting orders at various price levels andquantities thereof, etc., or not having or reflecting an impact on amarket or a subset or portion thereof. In one embodiment, an electronicorder book may be understood to be an electronic collection of theoutstanding or resting orders for a financial instrument.

For example, a request to place a trade may result in a responseindicative of the trade either being matched with, or being rested on anorder book to await, a suitable counter-order. This response may includea message directed solely to the trader who submitted the order toacknowledge receipt of the order and report whether it was matched, andthe extent thereto, or rested. The response may further include amessage to all market participants reporting a change in the order bookdue to the order, or an electronic data transaction result message. Thisresponse may take the form of a report of the specific change to theorder book, e.g., an order for quantity X at price Y was added to thebook (referred to, in one embodiment, as a Market By Order message), ormay simply report the result, e.g., price level Y now has orders for atotal quantity of Z (where Z is the sum of the previous resting quantityplus quantity X of the new order). In some cases, requests may elicit anon-impacting response, such as temporally proximate to the receipt ofthe request, and then cause a separate market-impact reflecting responseat a later time. For example, a stop order, fill or kill order (FOK),also known as an immediate or cancel order, or other conditional requestmay not have an immediate market impacting effect, if at all, until therequisite conditions are met.

An acknowledgement or confirmation of receipt, e.g., a non-marketimpacting communication, may be sent to the trader simply confirmingthat the order was received. Upon the conditions being met and a marketimpacting result thereof occurring, a market-impacting message may betransmitted as described herein both directly back to the submittingmarket participant and to all market participants (in a Market By Price“MBP”, or Market By Order “MBO”). It should be appreciated thatadditional conditions may be specified, such as a time or price limit,which may cause the order to be dropped or otherwise canceled and thatsuch an event may result in another non-market-impacting communicationinstead. In some implementations, market impacting communications may becommunicated separately from non-market impacting communications, suchas via a separate communications channel or feed.

For additional details and descriptions of different market data feeds,see U.S. Patent Publication No. 2017/0331774, filed on May 16, 2016,entitled “Systems and Methods for Consolidating Multiple Feed Data”,assigned to the assignee of the present application, the entirety ofwhich is incorporated by reference herein and relied upon.

It should be further appreciated that various types of market data feedsmay be provided which reflect different markets or aspects thereof.Market participants may then, for example, subscribe to receive thosefeeds of interest to them. For example, data recipient computing systemsmay choose to receive one or more different feeds. As market impactingcommunications usually tend to be more important to market participantsthan non-impacting communications, this separation may reduce congestionand/or noise among those communications having or reflecting an impacton a market or portion thereof. Furthermore, a particular market datafeed may only communicate information related to the top buy/sell pricesfor a particular product, referred to as “top of book” feed, e.g., onlychanges to the top 10 price levels are communicated. Such limitationsmay be implemented to reduce consumption of bandwidth and messagegeneration resources. In this case, while a request message may beconsidered market-impacting if it affects a price level other than thetop buy/sell prices, it will not result in a message being sent to themarket participants.

Examples of the various types of market data feeds which may be providedby electronic trading systems, such as the CME, in order to providedifferent types or subsets of market information or to provide suchinformation in different formats include Market By Order, Market Depth(also known as Market by Price to a designated depth of the book), e.g.,CME offers a 10-deep market by price feed, Top of Book (a single depthMarket by Price feed), and combinations thereof. There may also be allmanner of specialized feeds in terms of the content, i.e., providing,for example, derived data, such as a calculated index. Market data feedsmay be characterized as providing a “view” or “overview” of a givenmarket, an aggregation or a portion thereof or changes thereto. Forexample, a market data feed, such as a Market By Price (“MBP”) feed, mayconvey, with each message, the entire/current state of a market, orportion thereof, for a particular product as a result of one or moremarket impacting events. For example, an MBP message may convey a totalquantity of resting buy/sell orders at a particular price level inresponse to a new order being placed at that price. An MBP message mayconvey a quantity of an instrument which was traded in response to anincoming order being matched with one or more resting orders. MBPmessages may only be generated for events affecting a portion of amarket, e.g., only the top 10 resting buy/sell orders and, thereby, onlyprovide a view of that portion. As used herein, a market impactingrequest may be said to impact the “view” of the market as presented viathe market data feed.

An MBP feed may utilize different message formats for conveyingdifferent types of market impacting events. For example, when a neworder is rested on the order book, an MBP message may reflect thecurrent state of the price level to which the order was added, e.g., thenew aggregate quantity and the new aggregate number of resting orders.As can be seen, such a message conveys no information about theindividual resting orders, including the newly rested order, themselvesto the market participants. Only the submitting market participant, whoreceives a separate private message acknowledging the event, knows thatit was their order that was added to the book. Similarly, when a tradeoccurs, an MBP message may be sent which conveys the price at which theinstrument was traded, the quantity traded and the number ofparticipating orders, but may convey no information as to whoseparticular orders contributed to the trade. MBP feeds may further batchreporting of multiple events, i.e., report the result of multiple marketimpacting events in a single message.

Alternatively, a market data feed, referred to as a Market By Order(“MBO”) feed, may convey data reflecting a change that occurred to theorder book rather than the result of that change, e.g., that order ABCfor quantity X was added to price level Y or that order ABC and orderXYZ traded a quantity X at a price Y. In this case, the MBO messageidentifies only the change that occurred so a market participant wishingto know the current state of the order book must maintain their own copyand apply the change reflected in the message to know the current state.As can be seen, MBO messages may carry much more data than MBP messagesbecause MBO messages reflect information about each order, whereas MBPmessages contain information about orders affecting some predeterminedvalue levels. Furthermore, because specific orders, but not thesubmitting traders thereof, are identified, other market participantsmay be able to follow that order as it progresses through the market,e.g., as it is modified, canceled, traded, etc.

An MBP book data object may include information about multiple values.The MBP book data object may be arranged and structured so thatinformation about each value is aggregated together. Thus, for a givenvalue V (e.g., a price), the MBP book data object may aggregate all theinformation by value, such as for example, the number of orders having acertain position at value V, the quantity of total orders resting atvalue V, etc. Thus, the value field may be the key, or may be a uniquefield, within an MBP book data object. In one embodiment, the value foreach entry within the MBP book data object is different. In oneembodiment, information in an MBP book data object is presented in amanner such that the value field is the most granular field ofinformation.

An MBO book data object may include information about multiple orders.The MBO book data object may be arranged and structured so thatinformation about each order is represented. Thus, for a given order O,the MBO book data object may provide all of the information for order O.Thus, the order field may be the key, or may be a unique field, withinan MBO book data object. In one embodiment, the order ID for each entrywithin the MBO book data object is different. In one embodiment,information in an MBO book data object is presented in a manner suchthat the order field is the most granular field of information.

Thus, the MBO book data object may include data about unique orders,e.g., all unique resting orders for a product, and the MBP book dataobject may include data about unique values, e.g., up to a predeterminedlevel, e.g., top ten price or value levels, for a product.

It should be appreciated that the number, type and manner of market datafeeds provided by an electronic trading system are implementationdependent and may vary depending upon the types of products traded bythe electronic trading system, customer/trader preferences, bandwidthand data processing limitations, etc. and that all such feeds, nowavailable or later developed, are contemplated herein. MBP and MBO feedsmay refer to categories/variations of market data feeds, distinguishedby whether they provide an indication of the current state of a marketresulting from a market impacting event (MBP) or an indication of thechange in the current state of a market due to a market impacting event(MBO).

Messages, whether MBO or MBP, generated responsive to market impactingevents which are caused by a single order, such as a new order, an ordercancellation, an order modification, etc., are fairly simple and compactand easily created and transmitted. However, messages, whether MBO orMBP, generated responsive to market impacting events which are caused bymore than one order, such as a trade, may require the transmission of asignificant amount of data to convey the requisite information to themarket participants. For trades involving a large number of orders,e.g., a buy order for a quantity of 5000 which matches 5000 sell orderseach for a quantity of 1, a significant amount of information may needto be sent, e.g., data indicative of each of the 5000 trades that haveparticipated in the market impacting event.

In one embodiment, an exchange computing system may generate multipleorder book objects, one for each type of view that is published orprovided. For example, the system may generate an MBO book object and anMBP book object. It should be appreciated that each book object, or viewfor a product or market, may be derived from the MBO book object, whichincludes all the orders for a given financial product or market.

An inbound message may include an order that affects the MBO bookobject, the MBP book object, or both. An outbound message may includedata from one or more of the structures within the exchange computingsystem, e.g., the MBO book object queues or the MBP book object queues.

Furthermore, each participating trader needs to receive a notificationthat their particular order has traded. Continuing with the example,this may require sending 5001 individual trade notification messages, oreven 10,000+ messages where each contributing side (buy vs. sell) isseparately reported, in addition to the notification sent to all of themarket participants.

As detailed in U.S. Patent Publication No. 2015/0161727, the entirety ofwhich is incorporated by reference herein and relied upon, it may berecognized that trade notifications sent to all market participants mayinclude redundant information repeated for each participating trade anda structure of an MBP trade notification message may be provided whichresults in a more efficient communication of the occurrence of a trade.The message structure may include a header portion which indicates thetype of transaction which occurred, i.e., a trade, as well as othergeneral information about the event, an instrument portion whichcomprises data about each instrument which was traded as part of thetransaction, and an order portion which comprises data about eachparticipating order. In one embodiment, the header portion may include amessage type, Transaction Time, Match Event Indicator, and Number ofMarket Data Entries (“No. MD Entries”) fields. The instrument portionmay include a market data update action indicator (“MD Update Action”),an indication of the Market Data Entry Type (“MD Entry Type”), anidentifier of the instrument/security involved in the transaction(“Security ID”), a report sequence indicator (“Rpt Seq”), the price atwhich the instrument was traded (“MD Entry PX”), the aggregate quantitytraded at the indicated price (“ConsTradeQty”), the number ofparticipating orders (“NumberOfOrders”), and an identifier of theaggressor side (“Aggressor Side”) fields. The order portion may furtherinclude an identifier of the participating order (“Order ID”), describedin more detail below, and the quantity of the order traded (“MD EntrySize”) fields. It should be appreciated that the particular fieldsincluded in each portion are implementation dependent and that differentfields in addition to, or in lieu of, those listed may be includeddepending upon the implementation. It should be appreciated that theexemplary fields can be compliant with the FIX binary and/or FIX/FASTprotocol for the communication of the financial information.

The instrument portion contains a set of fields, e.g., seven fieldsaccounting for 23 bytes, which are repeated for each participatinginstrument. In complex trades, such as trades involving combinationorders or strategies, e.g., spreads, or implied trades, there may bemultiple instruments being exchanged among the parties. In oneembodiment, the order portion includes only one field, accounting for 4bytes, for each participating order which indicates the quantity of thatorder which was traded. As will be discussed below, the order portionmay further include an identifier of each order, accounting for anadditional 8 bytes, in addition to the quantity thereof traded. Asshould be appreciated, data which would have been repeated for eachparticipating order, is consolidated or otherwise summarized in theheader and instrument portions of the message thereby eliminatingredundant information and, overall, significantly reducing the size ofthe message.

The disclosed embodiments may be applicable to the use of either an MBPmarket data feed and/or an MBO market data feed.

IV. Matching and Transaction Processing

Market participants, e.g., traders, use software to send orders ormessages to the trading platform. The order identifies the product, thequantity of the product the trader wishes to trade, a price at which thetrader wishes to trade the product, and a direction of the order (i.e.,whether the order is a bid, i.e., an offer to buy, or an ask, i.e., anoffer to sell). It will be appreciated that there may be other ordertypes or messages that traders can send including requests to modify orcancel a previously submitted order.

The exchange computer system monitors incoming orders received therebyand attempts to identify, i.e., match or allocate, as described herein,one or more previously received, but not yet matched, orders, i.e.,limit orders to buy or sell a given quantity at a given price, referredto as “resting” orders, stored in an order book database, wherein eachidentified order is contra to the incoming order and has a favorableprice relative to the incoming order. An incoming order may be an“aggressor” order, i.e., a market order to sell a given quantity atwhatever may be the current resting bid order price(s) or a market orderto buy a given quantity at whatever may be the current resting ask orderprice(s). An incoming order may be a “market making” order, i.e., amarket order to buy or sell at a price for which there are currently noresting orders. In particular, if the incoming order is a bid, i.e., anoffer to buy, then the identified order(s) will be an ask, i.e., anoffer to sell, at a price that is identical to or higher than the bidprice. Similarly, if the incoming order is an ask, i.e., an offer tosell, the identified order(s) will be a bid, i.e., an offer to buy, at aprice that is identical to or lower than the offer price.

An exchange computing system may receive conditional orders or messagesfor a data object, where the order may include two prices or values: areference value and a stop value. A conditional order may be configuredso that when a product represented by the data object trades at thereference price, the stop order is activated at the stop value. Forexample, if the exchange computing system's order management module(described below) includes a stop order with a stop price of 5 and alimit price of 1 for a product, and a trade at 5 (i.e., the stop priceof the stop order) occurs, then the exchange computing system attemptsto trade at 1 (i.e., the limit price of the stop order). In other words,a stop order is a conditional order to trade (or execute) at the limitprice that is triggered (or elected) when a trade at the stop priceoccurs.

Stop orders also rest on, or are maintained in, an order book to monitorfor a trade at the stop price, which triggers an attempted trade at thelimit price. In some embodiments, a triggered limit price for a stoporder may be treated as an incoming order.

Upon identification (matching) of a contra order(s), a minimum of thequantities associated with the identified order and the incoming orderis matched and that quantity of each of the identified and incomingorders become two halves of a matched trade that is sent to a clearinghouse. The exchange computer system considers each identified order inthis manner until either all of the identified orders have beenconsidered or all of the quantity associated with the incoming order hasbeen matched, i.e., the order has been filled. If any quantity of theincoming order remains, an entry may be created in the order bookdatabase and information regarding the incoming order is recordedtherein, i.e., a resting order is placed on the order book for theremaining quantity to await a subsequent incoming order counter thereto.

It should be appreciated that in electronic trading systems implementedvia an exchange computing system, a trade price (or match value) maydiffer from (i.e., be better for the submitter, e.g., lower than asubmitted buy price or higher than a submitted sell price) the limitprice that is submitted, e.g., a price included in an incoming message,or a triggered limit price from a stop order.

As used herein, “better” than a reference value means lower than thereference value if the transaction is a purchase (or acquire)transaction, and higher than the reference value if the transaction is asell transaction. Said another way, for purchase (or acquire)transactions, lower values are better, and for sell (or relinquish)transactions, higher values are better.

Traders access the markets on a trading platform using trading softwarethat receives and displays at least a portion of the order book for amarket, i.e., at least a portion of the currently resting orders,enables a trader to provide parameters for an order for the producttraded in the market, and transmits the order to the exchange computersystem. The trading software typically includes a graphical userinterface to display at least a price and quantity of some of theentries in the order book associated with the market. The number ofentries of the order book displayed is generally preconfigured by thetrading software, limited by the exchange computer system, or customizedby the user. Some graphical user interfaces display order books ofmultiple markets of one or more trading platforms. The trader may be anindividual who trades on his/her behalf, a broker trading on behalf ofanother person or entity, a group, or an entity. Furthermore, the tradermay be a system that automatically generates and submits orders.

If the exchange computer system identifies that an incoming market ordermay be filled by a combination of multiple resting orders, e.g., theresting order at the best price only partially fills the incoming order,the exchange computer system may allocate the remaining quantity of theincoming, i.e., that which was not filled by the resting order at thebest price, among such identified orders in accordance withprioritization and allocation rules/algorithms, referred to as“allocation algorithms” or “matching algorithms,” as, for example, maybe defined in the specification of the particular financial product ordefined by the exchange for multiple financial products. Similarly, ifthe exchange computer system identifies multiple orders contra to theincoming limit order and that have an identical price which is favorableto the price of the incoming order, i.e., the price is equal to orbetter, e.g., lower if the incoming order is a buy (or instruction topurchase, or instruction to acquire) or higher if the incoming order isa sell (or instruction to relinquish), than the price of the incomingorder, the exchange computer system may allocate the quantity of theincoming order among such identified orders in accordance with thematching algorithms as, for example, may be defined in the specificationof the particular financial product or defined by the exchange formultiple financial products.

An exchange responds to inputs, such as trader orders, cancellation,etc., in a manner as expected by the market participants, such as basedon market data, e.g., prices, available counter-orders, etc., to providean expected level of certainty that transactions will occur in aconsistent and predictable manner and without unknown or unascertainablerisks. Accordingly, the method by which incoming orders are matched withresting orders must be defined so that market participants have anexpectation of what the result will be when they place an order or haveresting orders and an incoming order is received, even if the expectedresult is, in fact, at least partially unpredictable due to somecomponent of the process being random or arbitrary or due to marketparticipants having imperfect or less than all information, e.g.,unknown position of an order in an order book. Typically, the exchangedefines the matching/allocation algorithm that will be used for aparticular financial product, with or without input from the marketparticipants. Once defined for a particular product, thematching/allocation algorithm is typically not altered, except inlimited circumstance, such as to correct errors or improve operation, soas not to disrupt trader expectations. It will be appreciated thatdifferent products offered by a particular exchange may use differentmatching algorithms.

For example, a first-in/first-out (FIFO) matching algorithm, alsoreferred to as a “Price Time” algorithm, considers each identified ordersequentially in accordance with when the identified order was received.The quantity of the incoming order is matched to the quantity of theidentified order at the best price received earliest, then quantities ofthe next earliest best price orders, and so on until the quantity of theincoming order is exhausted. Some product specifications define the useof a pro-rata matching algorithm, wherein a quantity of an incomingorder is allocated to each of plurality of identified ordersproportionally. Some exchange computer systems provide a priority tocertain standing orders in particular markets. An example of such anorder is the first order that improves a price (i.e., improves themarket) for the product during a trading session. To be given priority,the trading platform may require that the quantity associated with theorder is at least a minimum quantity. Further, some exchange computersystems cap the quantity of an incoming order that is allocated to astanding order on the basis of a priority for certain markets. Inaddition, some exchange computer systems may give a preference to orderssubmitted by a trader who is designated as a market maker for theproduct. Other exchange computer systems may use other criteria todetermine whether orders submitted by a particular trader are given apreference. Typically, when the exchange computer system allocates aquantity of an incoming order to a plurality of identified orders at thesame price, the trading host allocates a quantity of the incoming orderto any orders that have been given priority. The exchange computersystem thereafter allocates any remaining quantity of the incoming orderto orders submitted by traders designated to have a preference, and thenallocates any still remaining quantity of the incoming order using theFIFO or pro-rata algorithms. Pro-rata algorithms used in some marketsmay require that an allocation provided to a particular order inaccordance with the pro-rata algorithm must meet at least a minimumallocation quantity. Any orders that do not meet or exceed the minimumallocation quantity are allocated to on a FIFO basis after the pro-rataallocation (if any quantity of the incoming order remains). Moreinformation regarding order allocation may be found in U.S. Pat. No.7,853,499, the entirety of which is incorporated by reference herein andrelied upon.

Other examples of matching algorithms which may be defined forallocation of orders of a particular financial product include: PriceExplicit Time; Order Level Pro Rata; Order Level Priority Pro Rata;Preference Price Explicit Time; Preference Order Level Pro Rata;Preference Order Level Priority Pro Rata; Threshold Pro-Rata; PriorityThreshold Pro-Rata; Preference Threshold Pro-Rata; Priority PreferenceThreshold Pro-Rata; and Split Price-Time Pro-Rata, which are describedin U.S. patent application Ser. No. 13/534,499, filed on Jun. 27, 2012,entitled “Multiple Trade Matching Algorithms,” published as U.S. PatentApplication Publication No. 2014/0006243 A1, the entirety of which isincorporated by reference herein and relied upon.

With respect to incoming orders, some traders, such as automated and/oralgorithmic traders, attempt to respond to market events, such as tocapitalize upon a mispriced resting order or other market inefficiency,as quickly as possible. This may result in penalizing the trader whomakes an errant trade, or whose underlying trading motivations havechanged, and who cannot otherwise modify or cancel their order fasterthan other traders can submit trades there against. It may consideredthat an electronic trading system that rewards the trader who submitstheir order first creates an incentive to either invest substantialcapital in faster trading systems, participate in the marketsubstantially to capitalize on opportunities (aggressor side/lower risktrading) as opposed to creating new opportunities (market making/higherrisk trading), modify existing systems to streamline business logic atthe cost of trade quality, or reduce one's activities and exposure inthe market. The result may be a lesser quality market and/or reducedtransaction volume, and corresponding thereto, reduced fees to theexchange.

With respect to resting orders, allocation/matching suitable restingorders to match against an incoming order can be performed, as describedherein, in many different ways. Generally, it will be appreciated thatallocation/matching algorithms are only needed when the incoming orderquantity is less than the total quantity of the suitable resting ordersas, only in this situation, is it necessary to decide which restingorder(s) will not be fully satisfied, which trader(s) will not get theirorders filled. It can be seen from the above descriptions of thematching/allocation algorithms, that they fall generally into threecategories: time priority/first-in-first-out (“FIFO”), pro rata, or ahybrid of FIFO and pro rata.

FIFO generally rewards the first trader to place an order at aparticular price and maintains this reward indefinitely. So if a traderis the first to place an order at price X, no matter how long that orderrests and no matter how many orders may follow at the same price, assoon as a suitable incoming order is received, that first trader will bematched first. This “first mover” system may commit other traders topositions in the queue after the first move traders. Furthermore, whileit may be beneficial to give priority to a trader who is first to placean order at a given price because that trader is, in effect, taking arisk, the longer that the trader's order rests, the less beneficial itmay be. For instance, it could deter other traders from adding liquidityto the marketplace at that price because they know the first mover (andpotentially others) already occupies the front of the queue.

With a pro rata allocation, incoming orders are effectively split amongsuitable resting orders. This provides a sense of fairness in thateveryone may get some of their order filled. However, a trader who tooka risk by being first to place an order (a “market turning” order) at aprice may end up having to share an incoming order with a much latersubmitted order. Furthermore, as a pro rata allocation distributes theincoming order according to a proportion based on the resting orderquantities, traders may place orders for large quantities, which theyare willing to trade but may not necessarily want to trade, in order toincrease the proportion of an incoming order that they will receive.This results in an escalation of quantities on the order book andexposes a trader to a risk that someone may trade against one of theseorders and subject the trader to a larger trade than they intended. Inthe typical case, once an incoming order is allocated against theselarge resting orders, the traders subsequently cancel the remainingresting quantity which may frustrate other traders. Accordingly, as FIFOand pro rata both have benefits and problems, exchanges may try to usehybrid allocation/matching algorithms which attempt to balance thesebenefits and problems by combining FIFO and pro rata in some manner.However, hybrid systems define conditions or fixed rules to determinewhen FIFO should be used and when pro rata should be used. For example,a fixed percentage of an incoming order may be allocated using a FIFOmechanism with the remainder being allocated pro rata.

V. Clearing House

The clearing house of an exchange clears, settles and guarantees matchedtransactions in contracts occurring through the facilities of theexchange. In addition, the clearing house establishes and monitorsfinancial requirements for clearing members and conveys certain clearingprivileges in conjunction with the relevant exchange markets. Once atrade event occurs, e.g., two of the transaction requests are matched,the result is that the market participants involved in the match havepositions which may be cleared by the exchange computing system. Theclearing house may store all the positions associated with a marketparticipant in a portfolio.

The clearing house establishes clearing level performance bonds(margins) for all products of the exchange and establishes minimumperformance bond requirements for customers of such products. Aperformance bond, also referred to as a margin requirement, correspondswith the funds that must be deposited by a customer with his or herbroker, by a broker with a clearing member or by a clearing member withthe clearing house, for the purpose of insuring the broker or clearinghouse against loss on open futures or options contracts. This is not apart payment on a purchase. The performance bond helps to ensure thefinancial integrity of brokers, clearing members and the exchange as awhole. The performance bond refers to the minimum dollar depositrequired by the clearing house from clearing members in accordance withtheir positions. Maintenance, or maintenance margin, refers to a sum,usually smaller than the initial performance bond, which must remain ondeposit in the customer's account for any position at all times. Theinitial margin is the total amount of margin per contract required bythe broker when a futures position is opened. A drop in funds below thislevel requires a deposit back to the initial margin levels, i.e., aperformance bond call. If a customer's equity in any futures positiondrops to or under the maintenance level because of adverse price action,the broker must issue a performance bond/margin call to restore thecustomer's equity. A performance bond call, also referred to as a margincall, is a demand for additional funds to bring the customer's accountback up to the initial performance bond level whenever adverse pricemovements cause the account to go below the maintenance.

The exchange derives its financial stability in large part by removingdebt obligations among market participants as they occur. This isaccomplished by determining a settlement price at the close of themarket each day for each contract and marking all open positions to thatprice, referred to as “mark to market.” Every contract is debited orcredited based on that trading session's gains or losses. As prices movefor or against a position, funds flow into and out of the tradingaccount. In the case of the CME, each business day by 6:40 a.m. Chicagotime, based on the mark-to-the-market of all open positions to theprevious trading day's settlement price, the clearing house pays to orcollects cash from each clearing member. This cash flow, known assettlement variation, is performed by CME's settlement banks based oninstructions issued by the clearing house. All payments to andcollections from clearing members are made in “same-day” funds. Inaddition to the 6:40 a.m. settlement, a daily intra-day mark-to-themarket of all open positions, including trades executed during theovernight GLOBEX®, the CME's electronic trading systems, trading sessionand the current day's trades matched before 11:15 a.m., is performedusing current prices. The resulting cash payments are made intra-day forsame day value. In times of extreme price volatility, the clearing househas the authority to perform additional intra-day mark-to-the-marketcalculations on open positions and to call for immediate payment ofsettlement variation. CME's mark-to-the-market settlement system maydiffer from the settlement systems implemented by many other financialmarkets, including the interbank, Treasury securities, over-the-counterforeign exchange and debt, options, and equities markets, whereparticipants regularly assume credit exposure to each other. In thosemarkets, the failure of one participant can have a ripple effect on thesolvency of the other participants. Conversely, CME's mark-to-the-marketsystem may not allow losses to accumulate over time or allow a marketparticipant the opportunity to defer losses associated with marketpositions.

While the disclosed embodiments may be described in reference to theCME, it should be appreciated that these embodiments are applicable toany exchange. Such other exchanges may include a clearing house that,like the CME clearing house, clears, settles and guarantees all matchedtransactions in contracts of the exchange occurring through itsfacilities. In addition, such clearing houses establish and monitorfinancial requirements for clearing members and convey certain clearingprivileges in conjunction with the relevant exchange markets.

The disclosed embodiments are also not limited to uses by a clearinghouse or exchange for purposes of enforcing a performance bond or marginrequirement. For example, a market participant may use the disclosedembodiments in a simulation or other analysis of a portfolio. In suchcases, the settlement price may be useful as an indication of a value atrisk and/or cash flow obligation rather than a performance bond. Thedisclosed embodiments may also be used by market participants or otherentities to forecast or predict the effects of a prospective position onthe margin requirement of the market participant.

VI. Market Segment Gateway and Business Transaction Processing

In one embodiment, the disclosed system may include a Market SegmentGateway (“MSG”) that is the point of ingress/entry and/oregress/departure for all transactions, i.e., the network traffic/packetscontaining the data therefore, specific to a single market at which theorder of receipt of those transactions may be ascribed. An MSG or MarketSegment Gateway may be utilized for the purpose of deterministicoperation of the market. The electronic trading system may includemultiple markets, and because the electronic trading system includes oneMSG for each market/product implemented thereby, the electronic tradingsystem may include multiple MSGs. For more detail on deterministicoperation in a trading system, see U.S. Patent Publication No.2015/0127513 entitled “Transactionally Deterministic High SpeedFinancial Exchange Having Improved, Efficiency, Communication,Customization, Performance, Access, Trading Opportunities, CreditControls, And Fault Tolerance” and filed on Nov. 7, 2013 (“the '513Publication”), the entire disclosure of which is incorporated byreference herein and relied upon.

For example, a participant may send a request for a new transaction,e.g., a request for a new order, to the MSG. The MSG extracts or decodesthe request message and determines the characteristics of the requestmessage.

The MSG may include, or otherwise be coupled with, a buffer, cache,memory, database, content addressable memory, data store or other datastorage mechanism, or combinations thereof, which stores data indicativeof the characteristics of the request message. The request is passed tothe transaction processing system, e.g., the match engine.

An MSG or Market Segment Gateway may be utilized for the purpose ofdeterministic operation of the market. Transactions for a particularmarket may be ultimately received at the electronic trading system viaone or more points of entry, e.g., one or more communicationsinterfaces, at which determinism may be applied, which as described maybe at the point where matching occurs, e.g., at each match engine (wherethere may be multiple match engines, each for a given product/market, ormoved away from the point where matching occurs and closer to the pointwhere the electronic trading system first becomes “aware” of theincoming transaction, such as the point where transaction messages,e.g., orders, ingress the electronic trading system. Generally, theterms “determinism” or “transactional determinism” may refer to theprocessing, or the appearance thereof, of orders in accordance withdefined business rules. Accordingly, as used herein, the point ofdeterminism may be the point at which the electronic trading systemascribes an ordering to incoming transactions/orders relative to otherincoming transactions/orders such that the ordering may be factored intothe subsequent processing, e.g., matching, of those transactions/ordersas will be described.

As described above, as used herein a business transaction may be definedas one or more operations or acts which are undertaken according to oneor more associated business rules (including industry, legal orregulatory requirements or customs) to accomplish a business orcommercial purpose, which may include compliance with industry,regulatory or legal requirements. A business transaction may beimplemented by one or more computer processing and/or databaseoperations/program steps, which themselves may be referred to astransactions. Business transactions, as defined by the associatedbusiness rules, may be characterized as deterministic in that they becharacterized by an interdependency or relationship which affects theirresult, such as a dependency on the order in which they are processed,such as a temporal order, and/or a dependency on real time processing,as defined by business rules, so as to effect the business/commercialpurpose and/or meet participant expectations, referred to herein as“transactional determinism.” Generally, a set of deterministictransactions will provide a particular result when executed in one orderand a different result when executed in a different order. In someapplications, deterministic processing may be preferred/prioritized overreal time processing.

For example, wherein the business rules define a first-in-first-out(“FIFO”) process for matching offers with counter-offers to effect anexchange or trade, when an offer transaction is received to which noprior counter offer transaction has been previously received, it shouldbe matched with the next suitable counter offer transaction receivedrather than a later received counter offer transactions. It will beappreciated that the processing of a given transaction may involvedelaying further processing of that transaction in favor of a laterreceived transaction, such as dependent upon conditions specified by theearlier transaction and/or the defined business rules. It will furtherbe appreciated that, at a minimum, any representation of the currentstate of a business environment, e.g. market, or changes thereto, inwhich the business transactions are transacted should present anaccurate reflection of the actual state or state change in accordancewith the defined business rules, so as to not mislead participants orprovide an unfair advantage. In the disclosed embodiments, the phrase“financial transaction” will refer to a business transaction involvingthe purchase or sale of financial instruments, such as futures contractsor options thereon, spread or other combination contracts and the like,as will be described. As was described above, electronic trading systemsgenerally define their business rules and then must ensure transactionaldeterminism in compliance therewith.

Generally, when the rate of business transaction processing is less thanthe underlying instructions processing capacity of the underlyinggeneral purpose processor, general performance optimizations implementedby the processor or operating system may be hidden or otherwiseimperceptible at the transactional level. That is, the processor is ableto perform these optimizations (e.g. page switches, instruction prefetch, branch mis-predictions, cache miss processing, error/packetrecovery) fast enough so as not to affect the executing businessapplication. However, as the rate and volume of transactions increases,contention for internal processor resources, such as memory bandwidth,also increases. Accordingly, the impact of internal optimizations on theexecuting application may no longer be imperceptible. In amultiprocessor environment, this impact may affect the ability tomaintain application tasks/processes, which are divided among multipleprocessors, in sync which each other which may result in out of orderexecution of one or more transactions.

In the exemplary embodiments, all transactions are ultimately receivedat the electronic trading system via a single point of entry, i.e. asingle communications interface, at which the disclosed embodimentsapply determinism, which as described is moved away from the point wherematching occurs and closer to the point where the electronic tradingsystem first becomes “aware” of the incoming transaction. This mayrequire improving the performance of this communications interface toprocess the influx of transactions without being overwhelmed. In someimplementations, more orders may be submitted by market participants viamore parallel inputs/channels/communications pathways implemented toincrease capacity and/or reduce resource contention. However, for manyof the reasons described above, parallel communication paths complicatedeterministic behavior, e.g. by creating opportunity, such a viaasymmetric delays among communications paths, for later transmitted orarriving transactions to overtake earlier arriving or transmittedtransactions, and may require mechanisms to discriminate among closelyreceived transactions and arbitrate among simultaneously, orsubstantially simultaneously, received transactions, e.g. transactionsreceived at the same time or received within a threshold of timeunresolvable by the system. Accordingly, mechanisms may be implementedto improve and impart deterministic handling of discrimination andarbitration among closely received transactions.

As was described above, to gain and maintain the trust and confidence ofmarket participants and encourage participation, electronic tradingsystems ideally attempt to offer a more efficient, fair and balancedmarket where market prices reflect a true consensus of the value oftraded products among the market participants, and which minimize, ifnot eliminate, surreptitious or overt subversion, influence of, ormanipulation by, any one or more market participants, intentional orotherwise, and unfair or inequitable advantages, with respect to accessto information or opportunities. To accomplish these goals, for example,electronic trading systems should operate in a deterministic, i.e. acausal, predictable, or otherwise expected, manner as understood andexperienced by the market participants, i.e. the customers of theExchange. Electronic trading systems which implement markets which areovertly or covertly inefficient, unfair or inequitable risk not onlylosing the trust, along with the patronage, of market participants, butalso increased regulatory scrutiny as well as potential criminal and/orcivil liability.

Accordingly, as described, the operators of electronic trading systems,alone or in conjunction with, or at the direction of, regulatory orindustry organizations, typically publish or otherwise promulgate rulesor regulations, referred to as business or operating rules, which governthe operation of the system. These rules define how, for example,multiple transactions are processed by the system where thosetransactions have relationships or dependencies there between which mayaffect the result of such processing. Such business rules may include,for example, order allocation rules, i.e. rules which dictate which ofmultiple competing resting orders will be matched with a particularincoming order counter thereto having insufficient quantity to fill allof the suitable resting orders. For example, under a first-in-first-outmethodology, the first order, of the competing resting orders, that wasreceived by the electronic trading system will be matched with theincoming counter-order and filled to the extent possible by theavailable quantity, with any residual quantity of the incoming counterorder then being allocated to the next received suitable competingresting order and so on until the available quantity of the incomingcounter order is exhausted. However, additional or alternativematching/allocation rules may be implemented as well, for example toensure fair and equal access, improve trading opportunities, etc., byallocating, such as proportionally, the available quantity of theincoming counter order among all, or a subset, of the competing restingorders until the available quantity is exhausted.

Once such business rules are established, or modified, marketparticipants will expect, and overseeing regulatory entities mayrequire, that the electronic trading system operate in accordancetherewith. That is, if the Exchange adopts a rule to give first arrivingorders priority over later arriving orders, a market participant whosubmits an earlier arriving order will expect their order to be filledprior to a later arriving order submitted by another market participant.It will be appreciated that these rules, by which operators of anelectronic trading system may choose to operate their system, may varyat the discretion of the operators, subject to regulatory concerns.Generally, the term “transactional determinism” may refer to theprocessing, or the appearance thereof, of orders in accordance with thedefined business rules.

In addition to efficiency, fairness and equity, electronic tradingsystems further provide significant performance improvements allowingfor rapid high volume transaction processing which benefits both theExchange and market participants. Metrics of electronic trading systemperformance include latency and throughput. Latency may be measured asthe response time of the Exchange. This can be measured in a number ofdifferent contexts: the time elapsed from when an order, or ordercancelation, is received to when a confirmation/acknowledgment ofreceipt is transmitted, from when an order is received to when anexecution notification is transmitted, or the time elapsed from when anorder is received to information about that order being disseminated inthe market data feed. Throughput may be measured as the maximum numberof orders or trades per second that the electronic trading system cansupport, i.e. receive and acknowledge, receive and match, etc.

Generally, market participants desire rapid market data updates, lowlatency/high throughput order processing, and prompt confirmations oftheir instructions to allow them to: competitively, frequently andconfidently evaluate, react to, and capitalize upon or, conversely,avoid, discrete, finite, fast moving/changing or ephemeral marketevents; leverage low return transactions via a high volume thereof;and/or otherwise coordinate, or synchronize their trading activitieswith other related concerns or activities, with less uncertainty withrespect to their order status. Higher volume capacity and transactionprocessing performance provides these benefits as well as, withoutdetrimentally affecting that capacity or performance, further improvesmarket access and market liquidity, such as by allowing forparticipation by more market participants, the provision of additionalfinancial products, and/or additional markets therefore, to meet thevarying needs of the market participants, and rapid identification ofadditional explicit and implicit intra- and inter-market tradingopportunities. The Exchange benefits, for example, from the increasedtransaction volume from which revenue is derived, e.g. via transactionfees.

Current electronic trading systems already offer significant performanceadvantages. However, increasing transaction volumes from an increasingnumber of market participants, implementation by some marketparticipants of algorithmic and/or high frequency trading methodologieswhereby high speed computers automatically monitor markets and react,usually in an overwhelming manner, to events, coupled with a continueddemand for ever-decreasing processing latencies and response times, isdriving a need for additional capacity and performance improvements tomaintain performance as experienced by each market participant and avoiddetrimental consequences, such as capacity exhaustion and inequitableaccess. For example, the increasing speed at which market participantsmay evaluate and respond to changes in market data, such as responsiveto a market event, is increasing the rate at which transactions arereceived by the electronic trading system, narrowing the time of receiptgap there between and necessitating a need for a higher degree ofdiscrimination so as to resolve the order in which those transactionsare received, upon which the deterministic operation of the electronictrading system may be based, e.g. for order allocation, etc.Furthermore, the addition, by electronic trading systems, of additionalchannels of communication in an effort to increase capacity andopportunity, along with increased bandwidth of each channel, allows formore transactions to be submitted over multiple parallel paths into thesystem. Accordingly, not only must the electronic trading systemdiscriminate among closely received incoming transactions, but mustfurther arbitrate among transactions received simultaneously, ortemporally so close together as to be considered simultaneouslyreceived, i.e. the difference in their time of receipt being too closeto measure by the implemented discrimination mechanisms, also referredto as “substantially simultaneously”.

In addition to increased capacity and lower latency, the global natureof business has further driven a need for fault tolerance to increaseavailability and reliability of electronic trading systems. Scheduledoutages must be minimized and unscheduled outages must be eliminated.

Furthermore, to implement the Exchange's clearing function, whichmitigates the concerns of market participants relating to performance bycounter parties, protects the interests of the Exchange and otherwiseadequately manages/mitigates risk, risk management systems havingcorresponding operational efficiency and performance are needed so as toprotect the Exchange from loss while minimizing impediments to marketoperations or distractions to market participants with ancillary andunnecessary tasks. In addition, increased transaction volume may furthertranslate into greater exposure for market participants requiringgreater amounts of capital to be posted to cover losses. Accordingly,more accurate and/or tailored risk assessment may be required to ensurethat only the necessary minimum amount of capital is required to beallocated by the market participants to cover potential losses and avoidundue encumbrances on/impediments to the ability of those marketparticipants to conduct their business.

Improved speed and efficiency also increases the speed at which problemsmay occur and propagate, or otherwise be exploited, such as where themarket ceases to operate as intended, i.e. the market no longer reflectsa true consensus of the value of traded products among the marketparticipants. Such problems are typically, but not always, evidenced byextreme market activity such as large changes in price, whether up ordown, over a short period of time or an extreme volume of trades takingplace. In particular, market participants, whether human or electronic,may not always react in a rational manner, such as when presented withimperfect information, when acting in fraudulent or otherwise unethicalmanner, and/or due to faulty training or design. For example, whilecommunications technologies may have improved, inequities still exist inboth access to information and access to opportunities to participate,which may not be due to any violations of legislative, regulatory and/orethical rules, e.g. some traders receive information before othertraders because they can afford faster communications channels, sometraders may be able to place trade orders more quickly than othersbecause they have faster computers. In many cases, irrational and/orexploitive trader behavior may be triggered by a market event, such as achange in price, creating a feedback loop where the initial irrationalreaction may then cause further market events, such as continued pricedrops, triggering further responses and resulting in an extreme changein the price of the traded product in a short period of time. High speedtrading exacerbates the problem as there may be little time fortraders/algorithmic trading systems, or those overseeing them, tocontemplate and temper their reactions before significant losses may beincurred. Furthermore, improved communications among traders facilitatesexploitation of information inequities and propagation of irrationalbehavior in one market to other markets as traders in those othermarkets react to the results of the irrational behavior. Marketprotection systems may therefore be needed to monitor and evaluatetrading activity, detect illegitimate/exploitive activity andappropriately react more quickly to mitigate the spread of problems,again without impeding legitimate market operation.

VII. Spread Instruments

Traders trading on an exchange including, for example, exchange computersystem 100, often desire to trade multiple financial instruments incombination. Each component of the combination may be called a leg.Traders can submit orders for individual legs or in some cases cansubmit a single order for multiple financial instruments in anexchange-defined combination. Such orders may be called a strategyorder, a spread order, or a variety of other names.

A spread instrument may involve the simultaneous purchase of onesecurity and sale of a related security, called legs, as a unit. Thelegs of a spread instrument may be options or futures contracts, orcombinations of the two. Trades in spread instruments are executed toyield an overall net position whose value, called the spread, depends onthe difference between the prices of the legs. Spread instruments may betraded in an attempt to profit from the widening or narrowing of thespread, rather than from movement in the prices of the legs directly.Spread instruments are either “bought” or “sold” depending on whetherthe trade will profit from the widening or narrowing of the spread,respectively. An exchange often supports trading of common spreads as aunit rather than as individual legs, thus ensuring simultaneousexecution of the two legs, eliminating the execution risk of one legexecuting but the other failing.

One example of a spread instrument is a calendar spread instrument. Thelegs of a calendar spread instrument differ in delivery date of theunderlier. The leg with the earlier occurring delivery date is oftenreferred to as the lead month contract. A leg with a later occurringdelivery date is often referred to as a deferred month contract. Anotherexample of a spread instrument is a butterfly spread instrument, whichincludes three legs having different delivery dates. The delivery datesof the legs may be equidistant to each other. The counterparty ordersthat are matched against such a combination order may be individual,“outright” orders or may be part of other combination orders.

In other words, an exchange may receive, and hold or let rest on thebooks, outright orders for individual contracts as well as outrightorders for spreads associated with the individual contracts. An outrightorder (for either a contract or for a spread) may include an outrightbid or an outright offer, although some outright orders may bundle manybids or offers into one message (often called a mass quote).

A spread is an order for the price difference between two contracts.This results in the trader holding a long and a short position in two ormore related futures or options on futures contracts, with the objectiveof profiting from a change in the price relationship. A typical spreadproduct includes multiple legs, each of which may include one or moreunderlying financial instruments. A butterfly spread product, forexample, may include three legs. The first leg may consist of buying afirst contract. The second leg may consist of selling two of a secondcontract. The third leg may consist of buying a third contract. Theprice of a butterfly spread product may be calculated as:Butterfly=Leg1−2*Leg2+Leg3

In the above equation, Leg1 equals the price of the first contract, Leg2equals the price of the second contract and Leg3 equals the price of thethird contract. Thus, a butterfly spread could be assembled from twointer-delivery spreads in opposite directions with the center deliverymonth common to both spreads.

A calendar spread, also called an intra-commodity spread, for futures isan order for the simultaneous purchase and sale of the same futurescontract in different contract months (i.e., buying a September CME S&P500® futures contract and selling a December CME S&P 500 futurescontract).

A crush spread is an order, usually in the soybean futures market, forthe simultaneous purchase of soybean futures and the sale of soybeanmeal and soybean oil futures to establish a processing margin. A crackspread is an order for a specific spread trade involving simultaneouslybuying and selling contracts in crude oil and one or more derivativeproducts, typically gasoline and heating oil. Oil refineries may trade acrack spread to hedge the price risk of their operations, whilespeculators attempt to profit from a change in the oil/gasoline pricedifferential.

A straddle is an order for the purchase or sale of an equal number ofputs and calls, with the same strike price and expiration dates. A longstraddle is a straddle in which a long position is taken in both a putand a call option. A short straddle is a straddle in which a shortposition is taken in both a put and a call option. A strangle is anorder for the purchase of a put and a call, in which the options havethe same expiration and the put strike is lower than the call strike,called a long strangle. A strangle may also be the sale of a put and acall, in which the options have the same expiration and the put strikeis lower than the call strike, called a short strangle. A pack is anorder for the simultaneous purchase or sale of an equally weighted,consecutive series of four futures contracts, quoted on an average netchange basis from the previous day's settlement price. Packs provide areadily available, widely accepted method for executing multiple futurescontracts with a single transaction. A bundle is an order for thesimultaneous sale or purchase of one each of a series of consecutivefutures contracts. Bundles provide a readily available, widely acceptedmethod for executing multiple futures contracts with a singletransaction.

VIII. Implication

Thus an exchange may match outright orders, such as individual contractsor spread orders (which as discussed herein could include multipleindividual contracts). The exchange may also imply orders from outrightorders. For example, exchange computer system 100 may derive, identifyand/or advertise, publish, display or otherwise make available fortrading orders based on outright orders.

As was described above, the financial instruments which are the subjectof the orders to trade, may include one or more component financialinstruments. While each financial instrument may have its own orderbook, i.e. market, in which it may be traded, in the case of a financialinstrument having more than one component financial instrument, thosecomponent financial instruments may further have their own order booksin which they may be traded. Accordingly, when an order for a financialinstrument is received, it may be matched against a suitable counterorder in its own order book or, possibly, against a combination ofsuitable counter orders in the order books the component financialinstruments thereof, or which share a common component financialinstrument. For example, an order for a spread contract comprisingcomponent financial instruments A and B may be matched against anothersuitable order for that spread contract. However, it may also be matchedagainst suitable separate counter orders for the A and for the Bcomponent financial instruments found in the order books therefore.Similarly, if an order for the A contract is received and suitable matchcannot be found in the A order book, it may be possible to match orderfor A against a combination of a suitable counter order for a spreadcontract comprising the A and B component financial instruments and asuitable counter order for the B component financial instrument. This isreferred to as “implication” where a given order for a financialinstrument may be matched via a combination of suitable counter ordersfor financial instruments which share common, or otherwiseinterdependent, component financial instruments. Implication increasesthe liquidity of the market by providing additional opportunities fororders to be traded. Increasing the number of transactions may furtherincrease the number of transaction fees collected by the electronictrading system.

The order for a particular financial instrument actually received from amarket participant, whether it comprises one or more component financialinstruments, is referred to as a “real” or “outright” order, or simplyas an outright. The one or more orders which must be synthesized andsubmitted into order books other than the order book for the outrightorder to create matches therein, are referred to as “implied” orders.

Upon receipt of an incoming order, the identification or derivation ofsuitable implied orders which would allow at least a partial trade ofthe incoming outright order to be executed is referred to as“implication” or “implied matching”, the identified orders beingreferred to as an “implied match.” Depending on the number of componentfinancial instruments involved, and whether those component financialinstruments further comprise component financial instruments of theirown, there may be numerous different implied matches identified whichwould allow the incoming order to be at least partially matched andmechanisms may be provided to arbitrate, e.g., automatically, amongthem, such as by picking the implied match comprising the least numberof component financial instruments or the least number of synthesizedorders.

Upon receipt of an incoming order, or thereafter, a combination of oneor more suitable/hypothetical counter orders which have not actuallybeen received but if they were received, would allow at least a partialtrade of the incoming order to be executed, may be, e.g., automatically,identified or derived and referred to as an “implied opportunity.” Aswith implied matches, there may be numerous implied opportunitiesidentified for a given incoming order. Implied opportunities areadvertised to the market participants, such as via suitable syntheticorders, e.g. counter to the desired order, being placed on therespective order books to rest (or give the appearance that there is anorder resting) and presented via the market data feed, electronicallycommunicated to the market participants, to appear available to trade inorder to solicit the desired orders from the market participants.Depending on the number of component financial instruments involved, andwhether those component financial instruments further comprise componentfinancial instruments of their own, there may be numerous impliedopportunities, the submission of a counter order in response thereto,that would allow the incoming order to be at least partially matched.

Implied opportunities, e.g. the advertised synthetic orders, mayfrequently have better prices than the corresponding real orders in thesame contract. This can occur when two or more traders incrementallyimprove their order prices in the hope of attracting a trade, sincecombining the small improvements from two or more real orders can resultin a big improvement in their combination. In general, advertisingimplied opportunities at better prices will encourage traders to enterthe opposing orders to trade with them. The more implied opportunitiesthat the match engine of an electronic trading system cancalculate/derive, the greater this encouragement will be and the morethe exchange will benefit from increased transaction volume. However,identifying implied opportunities may be computationally intensive. Oneresponse message may trigger the calculations of hundreds or thousandsof calculations to determine implied opportunities, which are thenpublished, e.g., as implied messages, via market data feeds. In a highperformance trading system where low transaction latency is important,it may be important to identify and advertise implied opportunitiesquickly so as to improve or maintain market participant interest and/ormarket liquidity.

For example, two different outright orders may be resting on the books,or be available to trade or match. The orders may be resting becausethere are no outright orders that match the resting orders. Thus, eachof the orders may wait or rest on the books until an appropriateoutright counteroffer comes into the exchange, or is placed by a user ofthe exchange. The orders may be for two different contracts that onlydiffer in delivery dates. It should be appreciated that such orderscould be represented as a calendar spread order. Instead of waiting fortwo appropriate outright orders to be received that would match the twoexisting or resting orders, the exchange computer system may identify ahypothetical spread order that, if entered into the system as a tradablespread order, would allow the exchange computer system to match the twooutright orders. The exchange may thus advertise or make available aspread order to users of the exchange system that, if matched with atradable spread order, would allow the exchange to also match the tworesting orders. Thus, the exchange computing system may be configured todetect that the two resting orders may be combined into an order in thespread instrument and accordingly creates an implied order.

In other words, the exchange may imply the counteroffer order by usingmultiple orders to create the counteroffer order. Examples of spreadsinclude implied IN, implied OUT, 2nd- or multiple-generation, crackspreads, straddle, strangle, butterfly, and pack spreads. Implied INspread orders are derived from existing outright orders in individuallegs. Implied OUT outright orders are derived from a combination of anexisting spread order and an existing outright order in one of theindividual underlying legs. Implied orders can fill in gaps in themarket and allow spreads and outright futures traders to trade in aproduct where there would otherwise have been little or no availablebids and asks.

For example, implied IN spreads may be created from existing outrightorders in individual contracts where an outright order in a spread canbe matched with other outright orders in the spread or with acombination of orders in the legs of the spread. An implied OUT spreadmay be created from the combination of an existing outright order in aspread and an existing outright order in one of the individualunderlying leg. An implied IN or implied OUT spread may be created whenan electronic matching system simultaneously works synthetic spreadorders in spread markets and synthetic orders in the individual legmarkets without the risk to the trader/broker of being double filled orfilled on one leg and not on the other leg.

By linking the spread and outright markets, implied spread tradingincreases market liquidity. For example, a buy in one contract month andan offer in another contract month in the same futures contract cancreate an implied market in the corresponding calendar spread. Anexchange may match an order for a spread product with another order forthe spread product. Some exchanges attempt to match orders for spreadproducts with multiple orders for legs of the spread products. With suchsystems, every spread product contract is broken down into a collectionof legs and an attempt is made to match orders for the legs.

Implied orders, unlike real orders, are generated by electronic tradingsystems. In other words, implied orders are computer generated ordersderived from real orders. The system creates the “derived” or “implied”order and provides the implied order as a market that may be tradedagainst. If a trader trades against this implied order, then the realorders that combined to create the implied order and the resultingmarket are executed as matched trades. Implied orders generally increaseoverall market liquidity. The creation of implied orders increases thenumber of tradable items, which has the potential of attractingadditional traders. Exchanges benefit from increased transaction volume.Transaction volume may also increase as the number of matched tradeitems increases.

Examples of implied spread trading include those disclosed in U.S.Patent Publication No. 2005/0203826, entitled “Implied Spread TradingSystem,” the entire disclosure of which is incorporated by referenceherein and relied upon. Examples of implied markets include thosedisclosed in U.S. Pat. No. 7,039,610, entitled “Implied Market TradingSystem,” the entire disclosure of which is incorporated by referenceherein and relied upon.

In some cases, the outright market for the deferred month or otherconstituent contract may not be sufficiently active to provide marketdata (e.g., bid-offer data) and/or trade data. Spread instrumentsinvolving such contracts may nonetheless be made available by theexchange. The market data from the spread instruments may then be usedto determine a settlement price for the constituent contract. Thesettlement price may be determined, for example, through a boundaryconstraint-based technique based on the market data (e.g., bid-offerdata) for the spread instrument, as described in U.S. Patent PublicationNo. 2015/0073962 entitled “Boundary Constraint-Based Settlement inSpread Markets”, the entire disclosure of which is incorporated byreference herein and relied upon. Settlement price determinationtechniques may be implemented to cover calendar month spread instrumentshaving different deferred month contracts.

Referring again to data transaction processing systems, a system maydepend on certain rules, logic, and inter-related objects and data. Intechnical and computing environments, a system may calculate values formultiple objects subject to rules, e.g., business or environment logic,associated with the objects. Certain object types may also depend onother object types. For example, a computing environment may includemultiple objects of different types, e.g., base objects and compositeobjects. A composite object as used herein is an object whose valuedepends on, is related to, or is influenced by, the values of otherobjects, such as base objects or other composite objects. For example, acomposite object may involve transactions between multiple, e.g., two,base objects. Or, a composite object may define a relationship betweenother objects. Thus, composite objects depend on the values of othersystem objects. In one embodiment, a composite object involves ordefines a transaction or relationship between at least two otherobjects. For example, a composite object involves or defines atransaction or relationship between two base objects. A base object mayrepresent an outright order associated with a financial instrument, anda composite object may represent a spread order associated with afinancial instrument.

IX. Computing Environment

The embodiments may be described in terms of a distributed computingsystem. The particular examples identify a specific set of componentsuseful in a futures and options exchange. However, many of thecomponents and inventive features are readily adapted to otherelectronic trading environments. The specific examples described hereinmay teach specific protocols and/or interfaces, although it should beunderstood that the principles involved may be extended to, or appliedin, other protocols and interfaces.

It should be appreciated that the plurality of entities utilizing orinvolved with the disclosed embodiments, e.g., the market participants,may be referred to by other nomenclature reflecting the role that theparticular entity is performing with respect to the disclosedembodiments and that a given entity may perform more than one roledepending upon the implementation and the nature of the particulartransaction being undertaken, as well as the entity's contractual and/orlegal relationship with another market participant and/or the exchange.

An exemplary trading network environment for implementing tradingsystems and methods is shown in FIG. 1. An exchange computer system 100receives messages that include orders and transmits market data relatedto orders and trades to users, such as via wide area network 162 and/orlocal area network 160 and computer devices 150, 152, 154, 156 and 158,as described herein, coupled with the exchange computer system 100.

Herein, the phrase “coupled with” is defined to mean directly connectedto or indirectly connected through one or more intermediate components.Such intermediate components may include both hardware and softwarebased components. Further, to clarify the use in the pending claims andto hereby provide notice to the public, the phrases “at least one of<A>, <B>, . . . and <N>” or “at least one of <A>, <B>, <N>, orcombinations thereof” are defined by the Applicant in the broadestsense, superseding any other implied definitions herebefore orhereinafter unless expressly asserted by the Applicant to the contrary,to mean one or more elements selected from the group comprising A, B, .. . and N, that is to say, any combination of one or more of theelements A, B, . . . or N including any one element alone or incombination with one or more of the other elements which may alsoinclude, in combination, additional elements not listed.

The exchange computer system 100 may be implemented with one or moremainframe, desktop or other computers, such as the example computer 200described herein with respect to FIG. 2. A user database 102 may beprovided which includes information identifying traders and other usersof exchange computer system 100, such as account numbers or identifiers,user names and passwords. An account data module 104 may be providedwhich may process account information that may be used during trades.

A match engine module 106 may be included to match bid and offer pricesand may be implemented with software that executes one or morealgorithms for matching bids and offers. A trade database 108 may beincluded to store information identifying trades and descriptions oftrades. In particular, trade database 108 may store informationidentifying the time that a trade took place and the contract price. Anorder book module 110 may be included to compute or otherwise determinecurrent bid and offer prices, e.g., in a continuous auction market, oralso operate as an order accumulation buffer for a batch auction market.

A market data module 112 may be included to collect market data andprepare the data for transmission to users. For example, the market datamodule 112 may prepare the market data feeds described herein.

A risk management module 114 may be included to compute and determine auser's risk utilization in relation to the user's defined riskthresholds. The risk management module 114 may also be configured todetermine risk assessments or exposure levels in connection withpositions held by a market participant. The risk management module 114may be configured to administer, manage or maintain one or moremargining mechanisms implemented by the exchange computer system 100.Such administration, management or maintenance may include managing anumber of database records reflective of margin accounts of the marketparticipants. In some embodiments, the risk management module 114implements one or more aspects of the disclosed embodiments, including,for instance, principal component analysis (PCA) based margining, inconnection with interest rate swap (IRS) portfolios.

A message management module 116 may be included to, among other things,receive, and extract orders from, electronic data transaction requestmessages. The message management module 116 may define a point ofingress into the exchange computer system 100 where messages are orderedand considered to be received by the system. This may be considered apoint of determinism in the exchange computer system 100 that definesthe earliest point where the system can ascribe an order of receipt toarriving messages. The point of determinism may or may not be at or nearthe demarcation point between the exchange computer system 100 and apublic/internet network infrastructure. The message management module116 processes messages by interpreting the contents of a message basedon the message transmit protocol, such as the transmission controlprotocol (“TCP”), to provide the content of the message for furtherprocessing by the exchange computer system.

The message management module 116 may also be configured to detectcharacteristics of an order for a transaction to be undertaken in anelectronic marketplace. For example, the message management module 116may identify and extract order content such as a price, product, volume,and associated market participant for an order. The message managementmodule 116 may also identify and extract data indicating an action to beexecuted by the exchange computer system 100 with respect to theextracted order. For example, the message management module 116 maydetermine the transaction type of the transaction requested in a givenmessage. A message may include an instruction to perform a type oftransaction. The transaction type may be, in one embodiment, arequest/offer/order to either buy or sell a specified quantity or unitsof a financial instrument at a specified price or value. The messagemanagement module 116 may also identify and extract other orderinformation and other actions associated with the extracted order. Allextracted order characteristics, other information, and associatedactions extracted from a message for an order may be collectivelyconsidered an order as described and referenced herein.

Order or message characteristics may include, for example, the state ofthe system after a message is received, arrival time (e.g., the time amessage arrives at the MSG or Market Segment Gateway), message type(e.g., new, modify, cancel), and the number of matches generated by amessage. Order or message characteristics may also include marketparticipant side (e.g., buyer or seller) or time in force (e.g., a gooduntil end of day order that is good for the full trading day, a gooduntil canceled ordered that rests on the order book until matched, or afill or kill order that is canceled if not filled immediately, or a filland kill order (FOK) that is filled to the maximum amount possible basedon the state of the order book at the time the FOK order is processed,and any remaining or unfilled/unsatisfied quantity is not stored on thebooks or allowed to rest).

An order processing module 118 may be included to decompose delta-based,spread instrument, bulk and other types of composite orders forprocessing by the order book module 110 and/or the match engine module106. The order processing module 118 may also be used to implement oneor more procedures related to clearing an order. The order may becommunicated from the message management module 116 to the orderprocessing module 118. The order processing module 118 may be configuredto interpret the communicated order, and manage the ordercharacteristics, other information, and associated actions as they areprocessed through an order book module 110 and eventually transacted onan electronic market. For example, the order processing module 118 maystore the order characteristics and other content and execute theassociated actions. In an embodiment, the order processing module 118may execute an associated action of placing the order into an order bookfor an electronic trading system managed by the order book module 110.In an embodiment, placing an order into an order book and/or into anelectronic trading system may be considered a primary action for anorder. The order processing module 118 may be configured in variousarrangements, and may be configured as part of the order book module110, part of the message management module 116, or as an independentfunctioning module.

As an intermediary to electronic trading transactions, the exchangebears a certain amount of risk in each transaction that takes place. Tothat end, the clearing house implements risk management mechanisms toprotect the exchange. One or more of the modules of the exchangecomputer system 100 may be configured to determine settlement prices forconstituent contracts, such as deferred month contracts, of spreadinstruments, such as for example, settlement module 120. A settlementmodule 120 (or settlement processor or other payment processor) may beincluded to provide one or more functions related to settling orotherwise administering transactions cleared by the exchange. Settlementmodule 120 of the exchange computer system 100 may implement one or moresettlement price determination techniques. Settlement-related functionsneed not be limited to actions or events occurring at the end of acontract term. For instance, in some embodiments, settlement-relatedfunctions may include or involve daily or other mark to marketsettlements for margining purposes. In some cases, the settlement module120 may be configured to communicate with the trade database 108 (or thememory(ies) on which the trade database 108 is stored) and/or todetermine a payment amount based on a spot price, the price of thefutures contract or other financial instrument, or other price data, atvarious times. The determination may be made at one or more points intime during the term of the financial instrument in connection with amargining mechanism. For example, the settlement module 120 may be usedto determine a mark to market amount on a daily basis during the term ofthe financial instrument. Such determinations may also be made on asettlement date for the financial instrument for the purposes of finalsettlement.

In some embodiments, the settlement module 120 may be integrated to anydesired extent with one or more of the other modules or processors ofthe exchange computer system 100. For example, the settlement module 120and the risk management module 114 may be integrated to any desiredextent. In some cases, one or more margining procedures or other aspectsof the margining mechanism(s) may be implemented by the settlementmodule 120.

A clearinghouse module 122 may be included as part of exchange computersystem 100 and configured to carry out clearinghouse operations.Clearinghouse module 122 may receive data from and/or transmit data totrade database 108 and/or other modules of computer system 100 regardingtrades of OTC FX forwards, futures contracts, futures contracts options,OTC options and contracts, and other financial products. Clearinghousemodule 122 may facilitate the financial product exchange computingsystem 100 acting as one of the parties to every traded contract orother product. For example, computer system 100 may match an offer byparty A to sell a financial product with a bid by party B to purchase alike financial product. Clearinghouse module 122 may then create afinancial product between party A and the exchange and an offsettingsecond financial product between the exchange and party B. As anotherexample, module 122 may maintain margin data with regard to clearingmembers and/or trading customers. As part of such margin-relatedoperations, module 122 may store and maintain data regarding the valuesof various contracts and other instruments, determine mark-to-market andfinal settlement amounts, confirm receipt and/or payment of amounts duefrom margin accounts, confirm satisfaction of final settlementobligations (physical or cash), etc. As discussed in further detailbelow, module 122 may compress the size of an exchange tradedderivatives portfolio.

One or more of the above-described modules of the exchange computersystem 100 may be used to gather or obtain data to support thesettlement price determination, as well as a subsequent marginrequirement determination. For example, the order book module 110 and/orthe market data module 112 may be used to receive, access, or otherwiseobtain market data, such as bid-offer values of orders currently on theorder books. The trade database 108 may be used to receive, access, orotherwise obtain trade data indicative of the prices and volumes oftrades that were recently executed in a number of markets. In somecases, transaction data (and/or bid/ask data) may be gathered orobtained from open outcry pits and/or other sources and incorporatedinto the trade and market data from the electronic trading system(s). Itshould be appreciated that concurrent processing limits may be definedby or imposed separately or in combination on one or more of the tradingsystem components.

The disclosed mechanisms may be implemented at any logical and/orphysical point(s), or combinations thereof, at which the relevantinformation/data (e.g., message traffic and responses thereto) may bemonitored or flows or is otherwise accessible or measurable, includingone or more gateway devices, modems, the computers or terminals of oneor more market participants, e.g., client computers, etc.

One skilled in the art will appreciate that one or more modulesdescribed herein may be implemented using, among other things, atangible computer-readable medium comprising computer-executableinstructions (e.g., executable software code). Alternatively, modulesmay be implemented as software code, firmware code, specificallyconfigured hardware or processors, and/or a combination of theaforementioned. For example, the modules may be embodied as part of anexchange 100 for financial instruments. It should be appreciated thedisclosed embodiments may be implemented as a different or separatemodule of the exchange computer system 100, or a separate computersystem coupled with the exchange computer system 100 so as to haveaccess to margin account record, pricing, and/or other data. Asdescribed herein, the disclosed embodiments may be implemented as acentrally accessible system or as a distributed system, e.g., where someof the disclosed functions are performed by the computer systems of themarket participants.

The trading network environment shown in FIG. 1 includes exemplarycomputer devices 150, 152, 154, 156 and 158 which depict differentexemplary methods or media by which a computer device may be coupledwith the exchange computer system 100 or by which a user maycommunicate, e.g., send and receive, trade or other informationtherewith. It should be appreciated that the types of computer devicesdeployed by traders and the methods and media by which they communicatewith the exchange computer system 100 is implementation dependent andmay vary and that not all of the depicted computer devices and/ormeans/media of communication may be used and that other computer devicesand/or means/media of communications, now available or later developedmay be used. Each computer device, which may comprise a computer 200described in more detail with respect to FIG. 2, may include a centralprocessor, specifically configured or otherwise, that controls theoverall operation of the computer and a system bus that connects thecentral processor to one or more conventional components, such as anetwork card or modem. Each computer device may also include a varietyof interface units and drives for reading and writing data or files andcommunicating with other computer devices and with the exchange computersystem 100. Depending on the type of computer device, a user caninteract with the computer with a keyboard, pointing device, microphone,pen device or other input device now available or later developed.

An exemplary computer device 150 is shown directly connected to exchangecomputer system 100, such as via a T1 line, a common local area network(LAN) or other wired and/or wireless medium for connecting computerdevices, such as the network 220 shown in FIG. 2 and described withrespect thereto. The exemplary computer device 150 is further shownconnected to a radio 168. The user of radio 168, which may include acellular telephone, smart phone, or other wireless proprietary and/ornon-proprietary device, may be a trader or exchange employee. The radiouser may transmit orders or other information to the exemplary computerdevice 150 or a user thereof. The user of the exemplary computer device150, or the exemplary computer device 150 alone and/or autonomously, maythen transmit the trade or other information to the exchange computersystem 100.

Exemplary computer devices 152 and 154 are coupled with a local areanetwork (“LAN”) 160 which may be configured in one or more of thewell-known LAN topologies, e.g., star, daisy chain, etc., and may use avariety of different protocols, such as Ethernet, TCP/IP, etc. Theexemplary computer devices 152 and 154 may communicate with each otherand with other computer and other devices which are coupled with the LAN160. Computer and other devices may be coupled with the LAN 160 viatwisted pair wires, coaxial cable, fiber optics or other wired orwireless media. As shown in FIG. 1, an exemplary wireless personaldigital assistant device (“PDA”) 158, such as a mobile telephone, tabletbased compute device, or other wireless device, may communicate with theLAN 160 and/or the Internet 162 via radio waves, such as via WiFi,Bluetooth and/or a cellular telephone based data communicationsprotocol. PDA 158 may also communicate with exchange computer system 100via a conventional wireless hub 164.

FIG. 1 also shows the LAN 160 coupled with a wide area network (“WAN”)162 which may be comprised of one or more public or private wired orwireless networks. In one embodiment, the WAN 162 includes the Internet162. The LAN 160 may include a router to connect LAN 160 to the Internet162. Exemplary computer device 156 is shown coupled directly to theInternet 162, such as via a modem, DSL line, satellite dish or any otherdevice for connecting a computer device to the Internet 162 via aservice provider therefore as is known. LAN 160 and/or WAN 162 may bethe same as the network 220 shown in FIG. 2 and described with respectthereto.

Users of the exchange computer system 100 may include one or more marketmakers 166 which may maintain a market by providing constant bid andoffer prices for a derivative or security to the exchange computersystem 100, such as via one of the exemplary computer devices depicted.The exchange computer system 100 may also exchange information withother match or trade engines, such as trade engine 170. One skilled inthe art will appreciate that numerous additional computers and systemsmay be coupled to exchange computer system 100. Such computers andsystems may include clearing, regulatory and fee systems.

The operations of computer devices and systems shown in FIG. 1 may becontrolled by computer-executable instructions stored on anon-transitory computer-readable medium. For example, the exemplarycomputer device 152 may store computer-executable instructions forreceiving order information from a user, transmitting that orderinformation to exchange computer system 100 in electronic messages,extracting the order information from the electronic messages, executingactions relating to the messages, and/or calculating values fromcharacteristics of the extracted order to facilitate matching orders andexecuting trades. In another example, the exemplary computer device 154may include computer-executable instructions for receiving market datafrom exchange computer system 100 and displaying that information to auser.

Numerous additional servers, computers, handheld devices, personaldigital assistants, telephones and other devices may also be connectedto exchange computer system 100. Moreover, one skilled in the art willappreciate that the topology shown in FIG. 1 is merely an example andthat the components shown in FIG. 1 may include other components notshown and be connected by numerous alternative topologies.

Referring now to FIG. 2, an illustrative embodiment of a generalcomputer system 200 is shown. The computer system 200 can include a setof instructions that can be executed to cause the computer system 200 toperform any one or more of the methods or computer based functionsdisclosed herein. The computer system 200 may operate as a standalonedevice or may be connected, e.g., using a network, to other computersystems or peripheral devices. Any of the components discussed herein,such as processor 202, may be a computer system 200 or a component inthe computer system 200. The computer system 200 may be specificallyconfigured to implement a match engine, margin processing, payment orclearing function on behalf of an exchange, such as the ChicagoMercantile Exchange, of which the disclosed embodiments are a componentthereof.

In a networked deployment, the computer system 200 may operate in thecapacity of a server or as a client user computer in a client-serveruser network environment, or as a peer computer system in a peer-to-peer(or distributed) network environment. The computer system 200 can alsobe implemented as or incorporated into various devices, such as apersonal computer (PC), a tablet PC, a set-top box (STB), a personaldigital assistant (PDA), a mobile device, a palmtop computer, a laptopcomputer, a desktop computer, a communications device, a wirelesstelephone, a land-line telephone, a control system, a camera, a scanner,a facsimile machine, a printer, a pager, a personal trusted device, aweb appliance, a network router, switch or bridge, or any other machinecapable of executing a set of instructions (sequential or otherwise)that specify actions to be taken by that machine. In a particularembodiment, the computer system 200 can be implemented using electronicdevices that provide voice, video or data communication. Further, whilea single computer system 200 is illustrated, the term “system” shallalso be taken to include any collection of systems or sub-systems thatindividually or jointly execute a set, or multiple sets, of instructionsto perform one or more computer functions.

As illustrated in FIG. 2, the computer system 200 may include aprocessor 202, e.g., a central processing unit (CPU), a graphicsprocessing unit (GPU), or both. The processor 202 may be a component ina variety of systems. For example, the processor 202 may be part of astandard personal computer or a workstation. The processor 202 may beone or more general processors, digital signal processors, specificallyconfigured processors, application specific integrated circuits, fieldprogrammable gate arrays, servers, networks, digital circuits, analogcircuits, combinations thereof, or other now known or later developeddevices for analyzing and processing data. The processor 202 mayimplement a software program, such as code generated manually (i.e.,programmed).

The computer system 200 may include a memory 204 that can communicatevia a bus 208. The memory 204 may be a main memory, a static memory, ora dynamic memory. The memory 204 may include, but is not limited to,computer readable storage media such as various types of volatile andnon-volatile storage media, including but not limited to random accessmemory, read-only memory, programmable read-only memory, electricallyprogrammable read-only memory, electrically erasable read-only memory,flash memory, magnetic tape or disk, optical media and the like. In oneembodiment, the memory 204 includes a cache or random access memory forthe processor 202. In alternative embodiments, the memory 204 isseparate from the processor 202, such as a cache memory of a processor,the system memory, or other memory. The memory 204 may be an externalstorage device or database for storing data. Examples include a harddrive, compact disc (“CD”), digital video disc (“DVD”), memory card,memory stick, floppy disc, universal serial bus (“USB”) memory device,or any other device operative to store data. The memory 204 is operableto store instructions executable by the processor 202. The functions,acts or tasks illustrated in the figures or described herein may beperformed by the programmed processor 202 executing the instructions 212stored in the memory 204. The functions, acts or tasks are independentof the particular type of instructions set, storage media, processor orprocessing strategy and may be performed by software, hardware,integrated circuits, firm-ware, micro-code and the like, operating aloneor in combination. Likewise, processing strategies may includemultiprocessing, multitasking, parallel processing and the like.

As shown, the computer system 200 may further include a display unit214, such as a liquid crystal display (LCD), an organic light emittingdiode (OLED), a flat panel display, a solid state display, a cathode raytube (CRT), a projector, a printer or other now known or later developeddisplay device for outputting determined information. The display 214may act as an interface for the user to see the functioning of theprocessor 202, or specifically as an interface with the software storedin the memory 204 or in the drive unit 206.

Additionally, the computer system 200 may include an input device 216configured to allow a user to interact with any of the components ofsystem 200. The input device 216 may be a number pad, a keyboard, or acursor control device, such as a mouse, or a joystick, touch screendisplay, remote control or any other device operative to interact withthe system 200.

In a particular embodiment, as depicted in FIG. 2, the computer system200 may also include a disk or optical drive unit 206. The disk driveunit 206 may include a computer-readable medium 210 in which one or moresets of instructions 212, e.g., software, can be embedded. Further, theinstructions 212 may embody one or more of the methods or logic asdescribed herein. In a particular embodiment, the instructions 212 mayreside completely, or at least partially, within the memory 204 and/orwithin the processor 202 during execution by the computer system 200.The memory 204 and the processor 202 also may include computer-readablemedia as discussed herein.

The present disclosure contemplates a computer-readable medium thatincludes instructions 212 or receives and executes instructions 212responsive to a propagated signal, so that a device connected to anetwork 220 can communicate voice, video, audio, images or any otherdata over the network 220. Further, the instructions 212 may betransmitted or received over the network 220 via a communicationinterface 218. The communication interface 218 may be a part of theprocessor 202 or may be a separate component. The communicationinterface 218 may be created in software or may be a physical connectionin hardware. The communication interface 218 is configured to connectwith a network 220, external media, the display 214, or any othercomponents in system 200, or combinations thereof. The connection withthe network 220 may be a physical connection, such as a wired Ethernetconnection or may be established wirelessly. Likewise, the additionalconnections with other components of the system 200 may be physicalconnections or may be established wirelessly.

The network 220 may include wired networks, wireless networks, orcombinations thereof. The wireless network may be a cellular telephonenetwork, an 802.11, 802.16, 802.20, or WiMax network. Further, thenetwork 220 may be a public network, such as the Internet, a privatenetwork, such as an intranet, or combinations thereof, and may utilize avariety of networking protocols now available or later developedincluding, but not limited to, TCP/IP based networking protocols.

Embodiments of the subject matter and the functional operationsdescribed in this specification can be implemented in digital electroniccircuitry, or in computer software, firmware, or hardware, including thestructures disclosed in this specification and their structuralequivalents, or in combinations of one or more of them. Embodiments ofthe subject matter described in this specification can be implemented asone or more computer program products, i.e., one or more modules ofcomputer program instructions encoded on a computer readable medium forexecution by, or to control the operation of, data processing apparatus.While the computer-readable medium is shown to be a single medium, theterm “computer-readable medium” includes a single medium or multiplemedia, such as a centralized or distributed database, and/or associatedcaches and servers that store one or more sets of instructions. The term“computer-readable medium” shall also include any medium that is capableof storing, encoding or carrying a set of instructions for execution bya processor or that cause a computer system to perform any one or moreof the methods or operations disclosed herein. The computer readablemedium can be a machine-readable storage device, a machine-readablestorage substrate, a memory device, or a combination of one or more ofthem. The term “data processing apparatus” encompasses all apparatus,devices, and machines for processing data, including by way of example aprogrammable processor, a computer, or multiple processors or computers.The apparatus can include, in addition to hardware, code that creates anexecution environment for the computer program in question, e.g., codethat constitutes processor firmware, a protocol stack, a databasemanagement system, an operating system, or a combination of one or moreof them.

In a particular non-limiting, exemplary embodiment, thecomputer-readable medium can include a solid-state memory such as amemory card or other package that houses one or more non-volatileread-only memories. Further, the computer-readable medium can be arandom access memory or other volatile re-writable memory. Additionally,the computer-readable medium can include a magneto-optical or opticalmedium, such as a disk or tapes or other storage device to capturecarrier wave signals such as a signal communicated over a transmissionmedium. A digital file attachment to an e-mail or other self-containedinformation archive or set of archives may be considered a distributionmedium that is a tangible storage medium. Accordingly, the disclosure isconsidered to include any one or more of a computer-readable medium or adistribution medium and other equivalents and successor media, in whichdata or instructions may be stored.

In an alternative embodiment, dedicated or otherwise specificallyconfigured hardware implementations, such as application specificintegrated circuits, programmable logic arrays and other hardwaredevices, can be constructed to implement one or more of the methodsdescribed herein. Applications that may include the apparatus andsystems of various embodiments can broadly include a variety ofelectronic and computer systems. One or more embodiments describedherein may implement functions using two or more specific interconnectedhardware modules or devices with related control and data signals thatcan be communicated between and through the modules, or as portions ofan application-specific integrated circuit. Accordingly, the presentsystem encompasses software, firmware, and hardware implementations.

In accordance with various embodiments of the present disclosure, themethods described herein may be implemented by software programsexecutable by a computer system. Further, in an exemplary, non-limitedembodiment, implementations can include distributed processing,component/object distributed processing, and parallel processing.Alternatively, virtual computer system processing can be constructed toimplement one or more of the methods or functionality as describedherein.

Although the present specification describes components and functionsthat may be implemented in particular embodiments with reference toparticular standards and protocols, the invention is not limited to suchstandards and protocols. For example, standards for Internet and otherpacket switched network transmission (e.g., TCP/IP, UDP/IP, HTML, HTTP,HTTPS) represent examples of the state of the art. Such standards areperiodically superseded by faster or more efficient equivalents havingessentially the same functions. Accordingly, replacement standards andprotocols having the same or similar functions as those disclosed hereinare considered equivalents thereof.

A computer program (also known as a program, software, softwareapplication, script, or code) can be written in any form of programminglanguage, including compiled or interpreted languages, and it can bedeployed in any form, including as a standalone program or as a module,component, subroutine, or other unit suitable for use in a computingenvironment. A computer program does not necessarily correspond to afile in a file system. A program can be stored in a portion of a filethat holds other programs or data (e.g., one or more scripts stored in amarkup language document), in a single file dedicated to the program inquestion, or in multiple coordinated files (e.g., files that store oneor more modules, sub programs, or portions of code). A computer programcan be deployed to be executed on one computer or on multiple computersthat are located at one site or distributed across multiple sites andinterconnected by a communication network.

The processes and logic flows described in this specification can beperformed by one or more programmable processors executing one or morecomputer programs to perform functions by operating on input data andgenerating output. The processes and logic flows can also be performedby, and apparatus can also be implemented as, special purpose logiccircuitry, e.g., an FPGA (field programmable gate array) or an ASIC(application specific integrated circuit).

Processors suitable for the execution of a computer program include, byway of example, both general and special purpose microprocessors, andanyone or more processors of any kind of digital computer. Generally, aprocessor will receive instructions and data from a read only memory ora random access memory or both. The essential elements of a computer area processor for performing instructions and one or more memory devicesfor storing instructions and data. Generally, a computer will alsoinclude, or be operatively coupled to receive data from or transfer datato, or both, one or more mass storage devices for storing data, e.g.,magnetic, magneto optical disks, or optical disks. However, a computerneed not have such devices. Moreover, a computer can be embedded inanother device, e.g., a mobile telephone, a personal digital assistant(PDA), a mobile audio player, a Global Positioning System (GPS)receiver, to name just a few. Computer readable media suitable forstoring computer program instructions and data include all forms ofnon-volatile memory, media and memory devices, including by way ofexample semiconductor memory devices, e.g., EPROM, EEPROM, and flashmemory devices; magnetic disks, e.g., internal hard disks or removabledisks; magneto optical disks; and CD ROM and DVD-ROM disks. Theprocessor and the memory can be supplemented by, or incorporated in,special purpose logic circuitry.

As used herein, the terms “microprocessor” or “general-purposeprocessor” (“GPP”) may refer to a hardware device that fetchesinstructions and data from a memory or storage device and executes thoseinstructions (for example, an Intel Xeon processor or an AMD Opteronprocessor) to then, for example, process the data in accordancetherewith. The term “reconfigurable logic” may refer to any logictechnology whose form and function can be significantly altered (i.e.,reconfigured) in the field post-manufacture as opposed to amicroprocessor, whose function can change post-manufacture, e.g. viacomputer executable software code, but whose form, e.g. thearrangement/layout and interconnection of logical structures, is fixedat manufacture. The term “software” may refer to data processingfunctionality that is deployed on a GPP. The term “firmware” may referto data processing functionality that is deployed on reconfigurablelogic. One example of a reconfigurable logic is a field programmablegate array (“FPGA”) which is a reconfigurable integrated circuit. AnFPGA may contain programmable logic components called “logic blocks”,and a hierarchy of reconfigurable interconnects that allow the blocks tobe “wired together”, somewhat like many (changeable) logic gates thatcan be inter-wired in (many) different configurations. Logic blocks maybe configured to perform complex combinatorial functions, or merelysimple logic gates like AND, OR, NOT and XOR. An FPGA may furtherinclude memory elements, which may be simple flip-flops or more completeblocks of memory.

To provide for interaction with a user, embodiments of the subjectmatter described in this specification can be implemented on a devicehaving a display, e.g., a CRT (cathode ray tube) or LCD (liquid crystaldisplay) monitor, for displaying information to the user and a keyboardand a pointing device, e.g., a mouse or a trackball, by which the usercan provide input to the computer. Other kinds of devices can be used toprovide for interaction with a user as well. Feedback provided to theuser can be any form of sensory feedback, e.g., visual feedback,auditory feedback, or tactile feedback. Input from the user can bereceived in any form, including acoustic, speech, or tactile input.

Embodiments of the subject matter described in this specification can beimplemented in a computing system that includes a back end component,e.g., a data server, or that includes a middleware component, e.g., anapplication server, or that includes a front end component, e.g., aclient computer having a graphical user interface or a Web browserthrough which a user can interact with an implementation of the subjectmatter described in this specification, or any combination of one ormore such back end, middleware, or front end components. The componentsof the system can be interconnected by any form or medium of digitaldata communication, e.g., a communication network. Examples ofcommunication networks include a local area network (“LAN”) and a widearea network (“WAN”), e.g., the Internet.

The computing system can include clients and servers. A client andserver are generally remote from each other and typically interactthrough a communication network. The relationship of client and serverarises by virtue of computer programs running on the respectivecomputers and having a client-server relationship to each other.

It should be appreciated that the disclosed embodiments may beapplicable to other types of messages depending upon the implementation.Further, the messages may comprise one or more data packets, datagramsor other collection of data formatted, arranged configured and/orpackaged in a particular one or more protocols, e.g., the FIX protocol,TCP/IP, Ethernet, etc., suitable for transmission via a network 214 aswas described, such as the message format and/or protocols described inU.S. Pat. No. 7,831,491 and U.S. Patent Publication No. 2005/0096999 A1,both of which are incorporated by reference herein in their entiretiesand relied upon. Further, the disclosed message management system may beimplemented using an open message standard implementation, such as FIX,FIX Binary, FIX/FAST, or by an exchange-provided API.

The embodiments described herein may utilize trade related electronicmessages such as mass quote messages, individual order messages,modification messages, cancellation messages, etc., so as to enacttrading activity in an electronic market. The trading entity and/ormarket participant may have one or multiple trading terminals associatedwith the session. Furthermore, the financial instruments may befinancial derivative products. Derivative products may include futurescontracts, options on futures contracts, futures contracts that arefunctions of or related to other futures contracts, swaps, swaptions, orother financial instruments that have their price related to or derivedfrom an underlying product, security, commodity, equity, index, orinterest rate product. In one embodiment, the orders are for optionscontracts that belong to a common option class. Orders may also be forbaskets, quadrants, other combinations of financial instruments, etc.The option contracts may have a plurality of strike prices and/orcomprise put and call contracts. A mass quote message may be received atan exchange. As used herein, an exchange computing system 100 includes aplace or system that receives and/or executes orders.

In an embodiment, a plurality of electronic messages is received fromthe network. The plurality of electronic messages may be received at anetwork interface for the electronic trading system. The plurality ofelectronic messages may be sent from market participants. The pluralityof messages may include order characteristics and be associated withactions to be executed with respect to an order that may be extractedfrom the order characteristics. The action may involve any action asassociated with transacting the order in an electronic trading system.The actions may involve placing the orders within a particular marketand/or order book of a market in the electronic trading system.

In an embodiment, an incoming transaction may be received. The incomingtransaction may be from, and therefore associated with, a marketparticipant of an electronic market managed by an electronic tradingsystem. The transaction may involve an order as extracted from areceived message, and may have an associated action. The actions mayinvolve placing an order to buy or sell a financial product in theelectronic market, or modifying or deleting such an order. In anembodiment, the financial product may be based on an associatedfinancial instrument which the electronic market is established totrade.

In an embodiment, the action associated with the transaction isdetermined. For example, it may be determined whether the incomingtransaction comprises an order to buy or sell a quantity of theassociated financial instrument or an order to modify or cancel anexisting order in the electronic market. Orders to buy or sell andorders to modify or cancel may be acted upon differently by theelectronic market. For example, data indicative of differentcharacteristics of the types of orders may be stored.

In an embodiment, data relating to the received transaction is stored.The data may be stored in any device, or using any technique, operableto store and provide recovery of data. For example, a memory 204 orcomputer readable medium 210, may be used to store data, as is describedwith respect to FIG. 2 in further detail herein. Data may be storedrelating received transactions for a period of time, indefinitely, orfor a rolling most recent time period such that the stored data isindicative of the market participant's recent activity in the electronicmarket.

If and/or when a transaction is determined to be an order to modify orcancel a previously placed, or existing, order, data indicative of theseactions may be stored. For example, data indicative of a running countof a number or frequency of the receipt of modify or cancel orders fromthe market participant may be stored. A number may be a total number ofmodify or cancel orders received from the market participant, or anumber of modify or cancel orders received from the market participantover a specified time. A frequency may be a time based frequency, as ina number of cancel or modify orders per unit of time, or a number ofcancel or modify orders received from the market participant as apercentage of total transactions received from the participant, whichmay or may not be limited by a specified length of time.

If and/or when a transaction is determined to be an order to buy or sella financial product, or financial instrument, other indicative data maybe stored. For example, data indicative of quantity and associated priceof the order to buy or sell may be stored.

Data indicative of attempts to match incoming orders may also be stored.The data may be stored in any device, or using any technique, operableto store and provide recovery of data. For example, a memory 204 orcomputer readable medium 210, may be used to store data, as is describedwith respect to FIG. 2. The acts of the process as described herein mayalso be repeated. As such, data for multiple received transactions formultiple market participants may be stored and used as describe herein.

The order processing module 118 may also store data indicative ofcharacteristics of the extracted orders. For example, the orderprocessing module may store data indicative of orders having anassociated modify or cancel action, such as by recording a count of thenumber of such orders associated with particular market participants.The order processing module may also store data indicative of quantitiesand associated prices of orders to buy or sell a product placed in themarket order book 110, as associated with particular marketparticipants.

Also, the order processing module 118 may be configured to calculate andassociate with particular orders a value indicative of an associatedmarket participant's market activity quality, which is a valueindicative of whether the market participant's market activity increasesor tends to increase liquidity of a market. This value may be determinedbased on the price of the particular order, previously stored quantitiesof orders from the associated market participant, the previously storeddata indicative of previously received orders to modify or cancel asassociated with the market participant, and previously stored dataindicative of a result of the attempt to match previously receivedorders stored in association with the market participant. The orderprocessing module 118 may determine or otherwise calculate scoresindicative of the quality value based on these stored extracted ordercharacteristics.

Further, electronic trading systems may perform actions on orders placedfrom received messages based on various characteristics of the messagesand/or market participants associated with the messages. These actionsmay include matching the orders either during a continuous auctionprocess, or at the conclusion of a collection period during a batchauction process. The matching of orders may be by any technique.

The matching of orders may occur based on a priority indicated by thecharacteristics of orders and market participants associated with theorders. Orders having a higher priority may be matched before orders ofa lower priority. Such priority may be determined using varioustechniques. For example, orders that were indicated by messages receivedearlier may receive a higher priority to match than orders that wereindicated by messages received later. Also, scoring or grading of thecharacteristics may provide for priority determination. Data indicativeof order matches may be stored by a match engine and/or an orderprocessing module 118.

X. Order Book Object Data Structures

In one embodiment, the messages and/or values received for each objectmay be stored in queues according to value and/or priority techniquesimplemented by an exchange computing system 100. FIG. 3A illustrates anexample data structure 300, which may be stored in a memory or otherstorage device, such as the memory 204 or storage device 206 describedwith respect to FIG. 2, for storing and retrieving messages related todifferent values for the same action for an object. For example, datastructure 300 may be a set of queues or linked lists for multiple valuesfor an action, e.g., bid, on an object. Data structure 300 may beimplemented as a database. It should be appreciated that the system maystore multiple values for the same action for an object, for example,because multiple users submitted messages to buy specified quantities ofan object at different values. Thus, in one embodiment, the exchangecomputing system may keep track of different orders or messages forbuying or selling quantities of objects at specified values.

Although the present application contemplates using queue datastructures for storing messages in a memory, the implementation mayinvolve additional pointers, i.e., memory address pointers, or linkingto other data structures. Incoming messages may be stored at anidentifiable memory address. The transaction processor can traversemessages in order by pointing to and retrieving different messages fromthe different memories. Thus, messages that may be depictedsequentially, e.g., in FIG. 3B below, may actually be stored in memoryin disparate locations. The software programs implementing thetransaction processing may retrieve and process messages in sequencefrom the various disparate (e.g., random) locations. Thus, in oneembodiment, each queue may store different values, which could representprices, where each value points to or is linked to the messages (whichmay themselves be stored in queues and sequenced according to prioritytechniques, such as prioritizing by value) that will match at thatvalue. For example, as shown in FIG. 3A, all of the values relevant toexecuting an action at different values for an object are stored in aqueue. Each value in turn points to, e.g., a linked list or queuelogically associated with the values. The linked list stores themessages that instruct the exchange computing system to buy specifiedquantities of the object at the corresponding value.

The sequence of the messages in the message queues connected to eachvalue may be determined by exchange implemented priority techniques. Forexample, in FIG. 3A, messages M1, M2, M3 and M4 are associated withperforming an action (e.g., buying or selling) a certain number of units(may be different for each message) at Value 1. M1 has priority over M2,which has priority over M3, which has priority over M4. Thus, if acounter order matches at Value 1, the system fills as much quantity aspossible associated with M1 first, then M2, then M3, and then M4.

In the illustrated examples, the values may be stored in sequentialorder, and the best or lead value for a given queue may be readilyretrievable by and/or accessible to the disclosed system. Thus, in oneembodiment, the value having the best priority may be illustrated asbeing in the topmost position in a queue, although the system may beconfigured to place the best priority message in some otherpredetermined position. In the example of FIG. 3A, Value 1 is shown asbeing the best value or lead value, or the top of the book value, for anexample Action.

A lead acquisition value may be the best or lead value in an acquisitionqueue of an order book object, and a lead relinquish value may be thebest or lead value in a relinquish queue of the order book object.

FIG. 3B illustrates an example alternative data structure 310 forstoring and retrieving messages and related values. It should beappreciated that matches occur based on values, and so all the messagesrelated to a given value may be prioritized over all other messagesrelated to a different value. As shown in FIG. 3B, the messages may bestored in one queue and grouped by values according to the hierarchy ofthe values. The hierarchy of the values may depend on the action to beperformed.

For example, if a queue is a sell queue (e.g., the Action is Sell), thelowest value may be given the best priority and the highest value may begiven the lowest priority. Thus, as shown in FIG. 3B, if Value 1 islower than Value 2 which is lower than Value 3, Value 1 messages may beprioritized over Value 2, which in turn may be prioritized over Value 3.

Within Value 1, M1 is prioritized over M2, which in turn is prioritizedover M3, which in turn is prioritized over M4. Within Value 2, M5 isprioritized over M6, which in turn is prioritized over M7, which in turnis prioritized over M8. Within Value 3, M9 is prioritized over M10,which in turn is prioritized over M11, which in turn is prioritized overM12.

Alternatively, the messages may be stored in a tree-node data structurethat defines the priorities of the messages. In one embodiment, themessages may make up the nodes.

In one embodiment, the system may traverse through a number of differentvalues and associated messages when processing an incoming message.Traversing values may involve the processor loading each value, checkingthat value and deciding whether to load another value, i.e., byaccessing the address pointed at by the address pointer value. Inparticular, referring to FIG. 3B, if the queue is for selling an objectfor the listed Values 1, 2 and 3 (where Value 1 is lower than Value 2which is lower than Value 3), and if the system receives an incomingaggressing order to buy quantity X at a Value 4 that is greater thanValues 1, 2, and 3, the system will fill as much of quantity X aspossible by first traversing through the messages under Value 1 (insequence M1, M2, M3, M4). If any of the quantity of X remains, thesystem traverses down the prioritized queue until all of the incomingorder is filled (e.g., all of X is matched) or until all of thequantities of M1 through M12 are filled. Any remaining, unmatchedquantity remains on the books, e.g., as a resting order at Value 4,which was the entered value or the message's value.

The system may traverse the queues and check the values in a queue, andupon finding the appropriate value, may locate the messages involved inmaking that value available to the system. When an outright messagevalue is stored in a queue, and when that outright message is involvedin a trade or match, the system may check the queue for the value, andthen may check the data structure storing messages associated with thatvalue.

In one embodiment, an exchange computing system may convert allfinancial instruments to objects. In one embodiment, an object mayrepresent the order book for a financial instrument. Moreover, in oneembodiment, an object may be defined by two queues, one queue for eachaction that can be performed by a user on the object. For example, anorder book converted to an object may be represented by an Ask queue anda Bid queue. Resting messages or orders associated with the respectivefinancial instrument may be stored in the appropriate queue and recalledtherefrom.

In one embodiment, the messages associated with objects may be stored inspecific ways depending on the characteristics of the various messagesand the states of the various objects in memory. For example, a systemmay hold certain resting messages in queue until the message is to beprocessed, e.g., the message is involved in a match. The order, sequenceor priority given to messages may depend on the characteristics of themessage. For example, in certain environments, messages may indicate anaction that a computer in the system should perform. Actions may becomplementary actions, or require more than one message to complete. Forexample, a system may be tasked with matching messages or actionscontained within messages. The messages that are not matched may bequeued by the system in a data queue or other structure, e.g., a datatree having nodes representing messages or orders.

The queues are structured so that the messages are stored in sequenceaccording to priority. Although the embodiments are disclosed as beingimplemented in queues, it should be understood that different datastructures such as for example linked lists or trees may also be used.

The system may include separate data structures, e.g., queues, fordifferent actions associated with different objects within the system.For example, in one embodiment, the system may include a queue for eachpossible action that can be performed on an object. The action may beassociated with a value. The system prioritizes the actions based inpart on the associated value.

For example, as shown in FIG. 3C, the order book module of a computingsystem may include several paired queues, such as queues Bid and Ask foran object 302 (e.g., Object A). The system may include two queues, orone pair of queues, for each object that is matched or processed by thesystem. In one embodiment, the system stores messages in the queues thathave not yet been matched or processed. FIG. 3C may be an implementationof the data structures disclosed in FIGS. 3A and/or 3B. Each queue mayhave a top of book, or lead, position, such as positions 304 and 306,which stores data that is retrievable.

The queues may define the priority or sequence in which messages areprocessed upon a match event. For example, two messages stored in aqueue may represent performing the same action at the same value. When athird message is received by the system that represents a matchingaction at the same value, the system may need to select one of the twowaiting, or resting, messages as the message to use for a match. Thus,when multiple messages can be matched at the same value, the exchangemay have a choice or some flexibility regarding the message that ismatched. The queues may define the priority in which orders that areotherwise equivalent (e.g., same action for the same object at the samevalue) are processed.

The system may include a pair of queues for each object, e.g., a bid andask queue for each object. Each queue may be for example implementedutilizing the data structure of FIG. 3B. The exchange may be able tospecify the conditions upon which a message for an object should beplaced in a queue. For example, the system may include one queue foreach possible action that can be performed on an object. The system maybe configured to process messages that match with each other. In oneembodiment, a message that indicates performing an action at a value maymatch with a message indicating performing a corresponding action at thesame value. Or, the system may determine the existence of a match whenmessages for the same value exist in both queues of the same object. Themessages may be received from the same or different users or traders.

The queues illustrated in FIG. 3C hold or store messages received by acomputing exchange, e.g., messages submitted by a user to the computingexchange, and waiting for a proper match. It should be appreciated thatthe queues may also hold or store implieds, e.g., implied messagesgenerated by the exchange system, such as messages implied in or impliedout as described herein. The system thus adds messages to the queues asthey are received, e.g., messages submitted by users, or generated,e.g., implied messages generated by the exchanges. The sequence orprioritization of messages in the queues is based on information aboutthe messages and the overall state of the various objects in the system.

When the data transaction processing system is implemented as anexchange computing system, as discussed above, different clientcomputers submit electronic data transaction request messages to theexchange computing system. Electronic data transaction request messagesinclude requests to perform a transaction on a data object, e.g., at avalue for a quantity. The exchange computing system includes atransaction processor, e.g., a hardware matching processor or matchengine, that matches, or attempts to match, pairs of messages with eachother. For example, messages may match if they contain counterinstructions (e.g., one message includes instructions to buy, the othermessage includes instructions to sell) for the same product at the samevalue. In some cases, depending on the nature of the message, the valueat which a match occurs may be the submitted value or a better value. Abetter value may mean higher or lower value depending on the specifictransaction requested. For example, a buy order may match at thesubmitted buy value or a lower (e.g., better) value. A sell order maymatch at the submitted sell value or a higher (e.g., better) value.

XI. Transaction Processor Data Structures

FIG. 4 illustrates an example embodiment of a data structure used toimplement match engine module 106. Match engine module 106 may include aconversion component 402, pre-match queue 404, match component 406,post-match queue 408 and publish component 410.

Although the embodiments are disclosed as being implemented in queues,it should be understood that different data structures, such as forexample linked lists or trees, may also be used. Although theapplication contemplates using queue data structures for storingmessages in a memory, the implementation may involve additionalpointers, i.e., memory address pointers, or linking to other datastructures. Thus, in one embodiment, each incoming message may be storedat an identifiable memory address. The transaction processing componentscan traverse messages in order by pointing to and retrieving differentmessages from the different memories. Thus, messages that may beprocessed sequentially in queues may actually be stored in memory indisparate locations. The software programs implementing the transactionprocessing may retrieve and process messages in sequence from thevarious disparate (e.g., random) locations.

The queues described herein may, in one embodiment, be structured sothat the messages are stored in sequence according to time of receipt,e.g., they may be first in first out (FIFO) queues.

The match engine module 106 may be an example of a transactionprocessing system. The pre-match queue 404 may be an example of apre-transaction queue. The match component 406 may be an example of atransaction component. The post-match queue 408 may be an example of apost-transaction queue. The publish component 410 may be an example of adistribution component. The transaction component may process messagesand generate transaction component results.

It should be appreciated that match engine module 106 may not includeall of the components described herein. For example, match engine module106 may only include pre-match queue 404 and match component 406. In oneembodiment, the latency detection system may detect how long a messagewaits in a pre-match queue 404 (e.g., latency), and compares the latencyto the maximum allowable latency associated with the message.

In one embodiment, the publish component may be a distribution componentthat can distribute data to one or more market participant computers. Inone embodiment, match engine module 106 operates according to a firstin, first out (FIFO) ordering. The conversion component 402 converts orextracts a message received from a trader via the Market Segment Gatewayor MSG into a message format that can be input into the pre-match queue404.

Messages from the pre-match queue may enter the match component 406sequentially and may be processed sequentially. In one regard, thepre-transaction queue, e.g., the pre-match queue, may be considered tobe a buffer or waiting spot for messages before they can enter and beprocessed by the transaction component, e.g., the match component. Thematch component matches orders, and the time a messages spends beingprocessed by the match component can vary, depending on the contents ofthe message and resting orders on the book. Thus, newly receivedmessages wait in the pre-transaction queue until the match component isready to process those messages. Moreover, messages are received andprocessed sequentially or in a first-in, first-out (FIFO) methodology.The first message that enters the pre-match or pre-transaction queuewill be the first message to exit the pre-match queue and enter thematch component. In one embodiment, there is no out-of-order messageprocessing for messages received by the transaction processing system.The pre-match and post-match queues are, in one embodiment, fixed insize, and any messages received when the queues are full may need towait outside the transaction processing system or be re-sent to thetransaction processing system.

The match component 406 processes an order or message, at which pointthe transaction processing system may consider the order or message ashaving been processed. The match component 406 may generate one messageor more than one message, depending on whether an incoming order wassuccessfully matched by the match component. An order message thatmatches against a resting order in the order book may generate dozens orhundreds of messages. For example, a large incoming order may matchagainst several smaller resting orders at the same price level. Forexample, if many orders match due to a new order message, the matchengine needs to send out multiple messages informing traders whichresting orders have matched. Or, an order message may not match anyresting order and only generate an acknowledgement message. Thus, thematch component 406 in one embodiment will generate at least onemessage, but may generate more messages, depending upon the activitiesoccurring in the match component. For example, the more orders that arematched due to a given message being processed by the match component,the more time may be needed to process that message. Other messagesbehind that given message will have to wait in the pre-match queue.

Messages resulting from matches in the match component 406 enter thepost-match queue 408. The post-match queue may be similar infunctionality and structure to the pre-match queue discussed above,e.g., the post-match queue is a FIFO queue of fixed size. As illustratedin FIG. 4, a difference between the pre- and post-match queues may bethe location and contents of the structures, namely, the pre-match queuestores messages that are waiting to be processed, whereas the post-matchqueue stores match component results due to matching by the matchcomponent. The match component receives messages from the pre-matchqueue, and sends match component results to the post-match queue. In oneembodiment, the time that results messages, generated due to thetransaction processing of a given message, spend in the post-match queueis not included in the latency calculation for the given message.

Messages from the post-match queue 408 enter the publish component 410sequentially and are published via the MSG sequentially. Thus, themessages in the post-match queue 408 are an effect or result of themessages that were previously in the pre-match queue 404. In otherwords, messages that are in the pre-match queue 404 at any given timewill have an impact on or affect the contents of the post-match queue408, depending on the events that occur in the match component 406 oncethe messages in the pre-match queue 404 enter the match component 406.

As noted above, the match engine module 106 in one embodiment operatesin a first in first out (FIFO) scheme. In other words, the first messagethat enters the match engine module 106 is the first message that isprocessed by the match engine module 106. Thus, the match engine module106 in one embodiment processes messages in the order the messages arereceived. In FIG. 4, as shown by the data flow arrow, data is processedsequentially by the illustrated structures from left to right, beginningat the conversion component 402, to the pre-match queue, to the matchcomponent 406, to the post-match queue 408, and to the publish component410. The overall transaction processing system operates in a FIFO schemesuch that data flows from element 402 to 404 to 406 to 408 to 410, inthat order. If any one of the queues or components of the transactionprocessing system experiences a delay, that creates a backlog for thestructures preceding the delayed structure. For example, if the match ortransaction component is undergoing a high processing volume, and if thepre-match or pre-transaction queue is full of messages waiting to enterthe match or transaction component, the conversion component may not beable to add any more messages to the pre-match or pre-transaction queue.

Messages wait in the pre-match queue. The time a message waits in thepre-match queue depends upon how many messages are ahead of that message(i.e., earlier messages), and how much time each of the earlier messagesspends being serviced or processed by the match component. Messages alsowait in the post-match queue. The time a message waits in the post-matchqueue depends upon how many messages are ahead of that message (i.e.,earlier messages), and how much time each of the earlier messages spendsbeing serviced or processed by the publish component. These wait timesmay be viewed as a latency that can affect a market participant'strading strategy.

After a message is published (after being processed by the componentsand/or queues of the match engine module), e.g., via a market data feed,the message becomes public information and is publicly viewable andaccessible. Traders consuming such published messages may act upon thosemessage, e.g., submit additional new input messages to the exchangecomputing system responsive to the published messages.

The match component attempts to match aggressing or incoming ordersagainst resting orders. If an aggressing order does not match anyresting orders, then the aggressing order may become a resting order, oran order resting on the books. For example, if a message includes a neworder that is specified to have a one-year time in force, and the neworder does not match any existing resting order, the new order willessentially become a resting order to be matched (or attempted to bematched) with some future aggressing order. The new order will thenremain on the books for one year. On the other hand, an order specifiedas a fill or kill (e.g., if the order cannot be filled or matched withan order currently resting on the books, the order should be canceled)will never become a resting order, because it will either be filled ormatched with a currently resting order, or it will be canceled. Theamount of time needed to process or service a message once that messagehas entered the match component may be referred to as a service time.The service time for a message may depend on the state of the orderbooks when the message enters the match component, as well as thecontents, e.g., orders, that are in the message.

In one embodiment, orders in a message are considered to be “locked in”,or processed, or committed, upon reaching and entering the matchcomponent. If the terms of the aggressing order match a resting orderwhen the aggressing order enters the match component, then theaggressing order will be in one embodiment guaranteed to match.

As noted above, the latency experienced by a message, or the amount oftime a message spends waiting to enter the match component, depends uponhow many messages are ahead of that message (i.e., earlier messages),and how much time each of the earlier messages spends being serviced orprocessed by the match component. The amount of time a match componentspends processing, matching or attempting to match a message dependsupon the type of message, or the characteristics of the message. Thetime spent inside the processor may be considered to be a service time,e.g., the amount of time a message spends being processed or serviced bythe processor.

The number of matches or fills that may be generated in response to anew order message for a financial instrument will depend on the state ofthe data object representing the electronic marketplace for thefinancial instrument. The state of the match engine can change based onthe contents of incoming messages.

It should be appreciated that the match engine's overall latency is inpart a result of the match engine processing the messages it receives.The match component's service time may be a function of the message type(e.g., new, modify, cancel), message arrival rate (e.g., how many ordersor messages is the match engine module receiving, e.g., messages persecond), message arrival time (e.g., the time a message hits the inboundMSG or market segment gateway), number of fills generated (e.g., howmany fills were generated due to a given message, or how many ordersmatched due to an aggressing or received order), or number of Mass Quoteentries (e.g., how many of the entries request a mass quote).

In one embodiment, the time a message spends: being converted in theconversion component 402 may be referred to as a conversion time;waiting in the pre-match queue 404 may be referred to as a wait untilmatch time; being processed or serviced in the match component 406 maybe referred to as a matching time; waiting in the post-match queue 408may be referred to as a wait until publish time; and being processed orpublished via the publish component 410 may be referred to as apublishing time.

It should be appreciated that the latency may be calculated, in oneembodiment, as the sum of the conversion time and wait until match time.Or, the system may calculate latency as the sum of the conversion time,wait until match time, matching time, wait until publish time, andpublishing time. In systems where some or all of those times arenegligible, or consistent, a measured latency may only include the sumof some of those times. Or, a system may be designed to only calculateone of the times that is the most variable, or that dominates (e.g.,percentage wise) the overall latency. For example, some marketparticipants may only care about how long a newly sent message that isadded to the end of the pre-match queue will spend waiting in thepre-match queue. Other market participants may care about how long thatmarket participant will have to wait to receive an acknowledgement fromthe match engine that a message has entered the match component. Yetother market participants may care about how much time will pass fromwhen a message is sent to the match engine's conversion component towhen match component results exit or egress from the publish component.

XII. Data File Optimization

As described above, an exchange computing system may store portfolios ofopen positions, specifically, post-trade/post-match positions, forhundreds or thousands of clients, or market participants, in variousdata files. The positions are each the result of a trade match event,where an incoming order matches a resting order (e.g., resting in theorder book), and which are defined by the terms of the match. Theportfolios may include many different financial instruments/exchangetraded derivates that are listed by the exchange computing system and/orcleared by the exchange computing system. The exchange computing systemmay implement one or more computing systems (e.g., servers, datarepositories, processors, etc.) that may be used, at least in part, tostore or otherwise manage the data files of portfolios. The more dataelements (or line items, where each line item is an open position) inthe portfolio data file, the greater the strain on the exchangecomputing system, and the greater the computing resources necessary tohouse, manage, and process the portfolio data files. This may includemanaging and/or processing information associated with the portfolios.

Traders often use models that determine the risks associated with theirportfolios. Models used by traders often produce values that reflect theportfolio's sensitivity to changes in predefined variables, such asdelta, gamma, and vega. Traders adjust their portfolios, e.g., byentering into trades, based on the risks defined by the predefinedvariables, and not on the number of line items in the portfolio.Moreover, regulations may require traders to include certain positionsin a portfolio even if the positions do not change the risk profile ofthe portfolio. Traders may accordingly hold many positions in aportfolio that are a by-product of trading strategies or regulations.These practices have resulted in a strain on computer systems used toprocess and trade financial instruments.

As portfolios become larger for one or more of the exchange computingsystem's clients, the data storage capacity and/or processing powernecessary to process and/or store this information may approach astorage capacity and/or processing power limit of the currentlyinstalled hardware. As such, the exchange computing system may berequired to install more computing devices and/or upgrade existingcomputing components to handle the additional information storage and/orprocessing requirements.

It should be appreciated that some portfolios may include hundreds orthousands of line items, each line item represented as a data element.As described above, an increase in the number of financial instrumentsin a portfolio (e.g., an increase in the data elements) increases theoverall amount of computing resources (e.g., bandwidth, networkingsystems) necessary to manage the portfolio, and also generally degradesperformance of the computer system.

Many of these positions may be positions that either naturally offseteach other, such as a long (buy) and short (sell) position in the samefinancial instrument. To clarify the meaning of naturally offsettingpositions, for example, if a first portfolio includes a long positionand a short position of the same contract/financial instrument, the longposition and short position naturally offset each other. However, if aportfolio includes a long and short position in two financialinstruments, as well as a position in a spread instrument between thetwo financial instruments, then the three financial instruments may notnaturally offset each other even if considered altogether, the threefinancial instruments have a zero overall risk.

Some existing systems detect derivatives products on opposite sides ofthe market within a portfolio and automatically compress such contractsinto a reduced number of line items (e.g., a single line item, two lineitems, three line items, etc.) within the same contract and maturitydate. Further, one or more OTC algorithms may be used compress lineitems within the same maturity date. Other systems attempt to identifyopportunities to reduce the gross notional outstanding of exchangetraded derivatives and the technology overhead generated from thereporting process, such as by reducing the amount of data and/orsubsequent computing processes required to store the trades associatedwith one or more large portfolios.

Some systems offer margin offset based on whether a portfolio includesoffsetting positions in correlated products. For example, an exchangecomputing system may reduce a trader's margin requirement by a certainpercentage if the trader's portfolio includes correlated products.However, exchange computing system margin offsetting systems do notactually remove positions/line items from a portfolio. Instead, theoverall margin requirement is reduced. Accordingly, existing exchangecomputing systems can offer customers margin efficiency without reducingline items.

Existing systems do not adequately account for compression opportunitiesin portfolios where there is not a natural netting of positions, e.g.,where some of the positions have related risk characteristics but wherethose positions do not exactly or naturally offset each other. Thesetypes of portfolios exist as described above as a by-product of tradersadjusting their positions based on variables such as delta, vega andgamma, because this type of adjustment may be more efficient for marketparticipants than removing existing positions. To exit positions, atrader would have to enter into an offsetting trade, which would incur atransaction cost for executing the new offsetting trade. Additionally,submitting additional orders/electronic data transaction requestmessages for execution would incur additional computational costs forboth the traders as well as the exchange computing system whichprocesses the trades. It should be appreciated that from a trader'sperspective, it is not efficient to exit post-trade positions byexecuting additional trades. Because each change to a portfolio may beassociated with transactional financial costs as well as computationalcosts, a portfolio stored by the exchange computing system may havepositions that, when considered together, have zero overall risk.

Or, these types of portfolios may exist when a market maker places largenumbers of bids, asks, and related spreads which result in matches witha market taker's orders. These portfolios include positions that do notnaturally offset, but nevertheless include positions that economicallyoffset each other, or are flat from a risk perspective. For certainmarkets, the exchange computing system offers packages that traders canenter into, such as a spread position as well as the individual legsunderlying that spread position.

For example, in some markets, such as the energy market, tradingstrategies may dictate that a trader enter into a spread position, andalso into positions underlying that spread. Such strategies result in aportfolio including a large number of related positions, where eachposition triggers the computing and financial burdens described above.

For example, the exchange computing system 100 may list energy productsSingapore Fuel Oil 380 cst (Platts) (trading symbol SE) and European3.5% Fuel Oil (trading symbol UV). Exchange computing system 100 mayalso list an energy spread product Singapore Fuel Oil vs European 3.5%Fuel Oil (trading symbol EVC). A financial institution, marketparticipant or exchange computing system member may employ a tradingstrategy that results in purchasing/selling all three of the contractsSE, UV and EVC. A portfolio resulting from the trading strategy mayinclude the following three positions: long 30 SE, short 30 EVC, andshort 30 UV. It should be appreciated that the portfolio's overall riskis flat, because any movement of price of any one of the positions isbalanced out or offset by counter movements in the other positions.

However, the open interest remains on the books, which leads toregulatory capital requirements. Again, open interest is the position onthe market after a trade has matched. Basel III standardized capitalmodels require exchange traded derivatives products, futures and optionson futures, be capitalized on a “gross basis”. The “gross basis”approach may require certain financial institutions, e.g., banks, whotrade with the exchange computing system to aggregate positionsirrespective of the risk or offsetting nature of the positions, both inthe proprietary account and when providing customers clearing services.Accordingly, a portfolio may be subject to regulatory capitalrequirements even though the overall risk associated with the portfoliois essentially zero. A capital requirement is the amount of capital abank or other financial institution has to hold as required by financialregulators, such as the US Commodity Futures Trading Commission, theFederal Reserve System, or Office of the Comptroller of the Currency.

As such, clearing firms may allocate more capital than is necessary toaccount for the risk. Further, in doing so, excess computing power maybe used to support the large number of positions and to determinecapital requirements, resulting in networking inefficiency and/orcausing increased computing requirement costs in maintaining andupgrading servers and other network computing assets. This not onlyresults in a burdensome and inefficient amount of line items that haveto be processed, but also is extremely inefficient from a capitalperspective (i.e., the amount of money a market participant must setaside, per financial regulations).

By optimizing the size of one or more portfolio data files, the exchangecomputing system may be able to proactively manage the computingrequirements and the associated costs of storing, processing, and/ortransmitting the one or more portfolios, as well as reduce associatedcapital requirements.

Unnecessarily high capital requirements can limit the amount of tradingactivity of a market participant in several ways. Market participantshave a limit on how much capital can be set aside for capitalrequirements. As such, minimizing the size of portfolio data files,which can reduce capital requirements, can be beneficial for traders asit allows them to increase their participation and activity in themarkets. In some cases, a Futures Commissions Merchant or a clearingmember may impose a capital limit on the capital that a trader canutilize.

Referring now to FIG. 5, there are depicted aspects of a systemarchitecture in a block-diagram form and data flow between and amongvarious system components for operation of an exchange computing system100 including a system 500 for optimizing the size of a data file inaccordance with one embodiment. The data file may represent a portfolio,and may include data elements that correspond to line items or openpositions in the portfolio.

Clearinghouse module 122 of exchange computing system 100 includesoptimizer 500, which optimizes the size of the data file. Optimizer 500includes an expansion engine 502, which may be implemented as a separatecomponent or as one or more logic components, such as on an FPGA whichmay include a memory or reconfigurable component to store logic and aprocessing component to execute the stored logic, e.g. computer programlogic, stored in a memory, such as the memory 204 shown in FIG. 2 anddescribed in more detail above with respect thereto, or othernon-transitory computer readable medium, and executable by a processor,such as the processor 202 shown in FIG. 2 and described in more detailabove with respect thereto, to cause the processor to receive a datafile including a plurality of data elements, and to expand the data fileby generating additional data elements based on the data elementsincluded in the received data file.

For example, the optimizer receives a portfolio of exchange tradedderivatives, e.g., from the match engine module 106, and/or tradedatabase 108, where the portfolio includes post-trade/post-matchpositions associated with a market participant. The expansion engine 502may be configured to communicate with the user database 102 whichincludes more information about the market participant, and which may beused to determine whether positions are associated with a same commonmarket participant.

In one embodiment, the optimizer 500 processes a portfolio based on userpreferences, which are stored in the user database 102. For example, amarket participant may select specific financial instruments (e.g., aspread and its underlying legs) that, if present in the marketparticipant's portfolio (e.g., the market participant's portfolioincludes positions for those selected specific financial instruments),may be removed as discussed herein by the optimizer 500. Alternatively,a user may authorize the exchange computing system to algorithmicallysearch for opportunities to compress data elements, including searchingfor positions in the portfolio that do not naturally offset each otherbut when considered together have an overall economic risk of zero,e.g., the optimizer automatically searches a portfolio for a spreadposition comprising two financial instruments if the same portfolio alsoincludes positions in the two underlying legs. Accordingly, the type andextent of the compression that is performed by optimizer 500 may bebased on user preferences stored in user database 102 which iscommunicatively coupled to optimizer 500. The user preferences andsettings may be specified via a user interface of a user trading device,e.g., device 150.

In one embodiment, a trader may elect to optimize his or her derivativesportfolio via a user interface coupled to a trader computer system.Before a trader submits his or her portfolio to the clearing house ofthe exchange computing system, the trader may indicate, via the userinterface, that the exchange computing system should process theportfolio through the optimizer. Upon receiving a portfolio that ismarked as a portfolio that should be optimized, the exchange computingsystem automatically optimizes the portfolio as discussed herein.

The expansion engine 502 identifies spread positions in the portfolioand replaces each spread position with the legs underlying the spreadposition. FIG. 6A illustrates portfolio 602 including three differententries or positions 604 (long 30 SE), 606 (short 30 UV) and 608 (short30 EVC). Portfolio 602 may be associated with a total notional amount610 of $26,439,240, and a capital requirement 612 of $132,196. Althoughportfolio 602 is illustrated as having only three positions forexemplary purposes, it should be appreciated that portfolio 602 mayinclude hundreds or thousands of positions or line items, where many ofthe line items may be eliminated implementing the techniques describedherein.

FIG. 6B illustrates portfolio 622, which is the result of processing ofportfolio 602 by expansion engine 502. Portfolio 622 includes more lineitems than portfolio 602, and in particular, includes four line items.Line items 604 and 606 in portfolio 622 are the same as line items 604and 606 in portfolio 602. However, in portfolio 662, expansion engine502 has replaced line item 608 (from portfolio 602) with two new lineitems, namely, line items 624 and 626. In particular, the spreadposition 608 has been replaced by new positions 624 and 626, which arethe legs underlying position item 608.

Referring back to FIG. 5, optimizer 500 includes compression engine 504,which may be implemented as a separate component or as one or more logiccomponents, such as on an FPGA which may include a memory orreconfigurable component to store logic and a processing component toexecute the stored logic, e.g. computer program logic, stored in amemory, such as the memory 204 shown in FIG. 2 and described in moredetail above with respect thereto, or other non-transitory computerreadable medium, and executable by a processor, such as the processor202 shown in FIG. 2 and described in more detail above with respectthereto, to cause the processor to compress the size of the data file byreducing the number of data elements in the data file received from theexpansion engine 502.

Compression engine 504 receives portfolio 622 from the expansion engine502. Compression engine 504 performs a process where positions that arecounter to each other or that offset each other are deleted from thedata file associated with portfolio 622. For example, referring back toFIG. 6B, in portfolio 622, line item 604 would be offset by line item624, and line item 606 would be offset by line item 626, resulting in areduction of line items/data elements, and thus reducing the file sizeof the data file associated with portfolio 622. Again, althoughportfolio 622 is shown as having only four line items, portfolio 622 mayinclude hundreds or thousands of data elements, which would be eligiblefor compression by the compression engine 504.

Optimizer 500 may generate a new data file based on an existing datafile after each step performed by optimizer 500. For example, asdescribed in the above examples, portfolio 602 is deleted and portfolio622 is generated after the expansion step performed by the expansionengine 502. In one embodiment, the optimizer 500 may directly add andremove line items from a data file defining a portfolio. For example,instead of the expansion engine 502 generating a new data file/portfolio622 based on data file/portfolio 602, the expansion engine 502 maydirectly insert new data elements into the same data file/portfolio 602.

It should be appreciated that the optimizer 500 accordingly isconfigured to temporarily expand/increase the size of a portfolio datafile, before compressing/reducing the size of the portfolio data file.The result of processing portfolio 622 is that the entire portfolio isdeleted from memory. If portfolio 622 contained other data elements thatdid not offset each other, the portfolio 622 would be smaller in sizeafter being compressed by compression engine 504, but would not becompletely deleted.

The optimizer 500 may be implemented before or after attempting tocompress a portfolio using other know techniques/algorithms. In oneembodiment, the exchange computing system may perform other knowncompression techniques before optimizing the portfolio as described byoptimizer 500.

The disclosed optimizer reduces the number of line items/positions/dataelements in a portfolio, thereby reducing capital inefficiencies (e.g.,the capital requirement 612 which is high compared to the overall riskof positions 604, 606 and 608 considered together of essentially zero)as well as the unnecessary utilization of computing resources requiredto manage/store/transmit a large portfolio data file.

The disclosed embodiments enable the exchange computing system to offercustomers both margin requirement efficiency as well as capitalrequirement efficiency by compressing the portfolio as discussed herein.In addition, the data file containing the portfolio is compressed,enabling computational performance improvements (e.g., fewer computingresources required to maintain, manage, and transmit the data file).

It should be appreciated that the specific products/financialinstruments discussed here are for exemplary purposes only, and may bereplaced with other financial instruments. For example, the exchangecomputing system 100 may list energy products WTI Financial Futures(trading symbol CS) and Brent Financial Futures (trading symbol CY).Exchange computing system 100 may also list an energy spread productWTI—Brent Fin. Futures (trading symbol BK).

A financial institution, market participant or exchange computing systemmember may employ a trading strategy that results in purchasing/sellingall three of the contracts CS, CY and BK, and a portfolio resulting fromthe trading strategy may include positions in the three contracts. Thedisclosed embodiments may be implemented, as discussed herein, to reducethe size of a portfolio data file including data elements for thosepositions.

In one embodiment, optimizer 500 may optimize a derivatives portfolioautomatically. For example, a market participant may transmit a datafile including a plurality of data elements to the exchange computingsystem 100. The exchange computing system 100 may automatically processthe portfolio implementing the disclosed optimizer. For example, theoptimizer 500 may expand the portfolio by generating multiple new dataelements. The new data elements may replace some of the original dataelements in the portfolio. It should be appreciated that due to theexpansion engine of the optimizer, the size of the portfolio/data fileis increased. The expanded portfolio is then compressed by the optimizer500 by identifying offsetting positions. The specific situations andcircumstances controlling whether positions offset each other may bedefined by an administrator or operator of the exchange computingsystem, or alternatively by a trader/market participant. For example,two positions may offset each other if they are counter transactions(e.g., one buy and one sell) for the same quantity of a financialinstrument. Whether a market participant, or the exchange computingsystem, considers that positions are offsettable may be based oncriteria, and even positions that are not exact opposites of each othermay be considered offsettable. The exchange computing systemautomatically compresses the portfolio and determines the capitalregulatory requirements based on the compressed portfolio.

In an embodiment, the optimization system includes two compressionengines, instead of an expansion engine and a compression engine.Referring now to FIG. 7, there are depicted aspects of a systemarchitecture in a block-diagram form and data flow between and amongvarious system components for operation of an exchange computing system100 including a system 700 for optimizing the size of a data file inaccordance with one embodiment.

Clearinghouse module 122 of exchange computing system 100 includesoptimizer 700, which optimizes the size of the data file. Optimizer 700includes a plurality of compression engines 702 and 704. Compressionengine 702 may be implemented as a separate component or as one or morelogic components, such as on an FPGA which may include a memory orreconfigurable component to store logic and a processing component toexecute the stored logic, e.g. computer program logic, stored in amemory, such as the memory 204 shown in FIG. 2 and described in moredetail above with respect thereto, or other non-transitory computerreadable medium, and executable by a processor, such as the processor202 shown in FIG. 2 and described in more detail above with respectthereto, to cause the processor to receive a data file including aplurality of data elements, and to identify a plurality of data elementsthat can be represented by a few number of data elements, e.g., toidentify financial instruments that are the underlying legs of a spreadfinancial instrument, and to replace the underlying leg financialinstruments in the portfolio data file with a new spread financialinstrument. For example, the compression engine 702 identifies multipleleg line items in a portfolio that can be represented as a single spreadline item, and replaces the underlying legs with the spread position.

Compression engine 704 may be implemented as a separate component or asone or more logic components, such as on an FPGA which may include amemory or reconfigurable component to store logic and a processingcomponent to execute the stored logic, e.g. computer program logic,stored in a memory, such as the memory 204 shown in FIG. 2 and describedin more detail above with respect thereto, or other non-transitorycomputer readable medium, and executable by a processor, such as theprocessor 202 shown in FIG. 2 and described in more detail above withrespect thereto, to cause the processor to compress the size of the datafile by reducing the number of data elements in the data file receivedfrom the compression engine 702.

It should be appreciated that the exchange computing system may listseveral spread financial instruments that are comprised of commonunderlying legs. In other words, a financial instrument may be anunderlying leg for two different spreads. For example, a marketparticipant portfolio data file may include positions in each of: spreadfinancial instruments AB (composed of underlying leg financialinstruments A and B) and AC (composed of underlying leg financialinstruments A and C) and leg financial instruments A, B and C.Accordingly, the disclosed optimization system may be able to expandeach of the spread positions into constituent leg positions (e.g., AB isexpanded to A and B; AC is expanded to A and C), and then compress theportfolio data file by offsetting the leg financial instruments againsteach other (e.g., A line items are netted against each other if they canoffset each other). In one embodiment, the optimization systemprioritizes the offsetting of financial instruments that completelyeliminates line items. For example, if there are several different lineitems related to financial instrument A that can offset each other, theoptimization system prioritizes offsetting the A position with thelowest quantity because that position has the highest likelihood ofbeing completely eliminated from the portfolio, i.e., the data elementcan be deleted from the data file.

FIG. 8 shows a portion of an illustrative system 800 for reducing thesize of a portfolio including a plurality of exchange traded derivativesaccording to at least some embodiments. In some cases, the illustrativesystem 800 may include a financial institution computing system 810communicatively coupled to a clearinghouse computer system 840 via anetwork 805 (e.g., WAN 162, LAN 160, etc.). The financial institutioncomputing system 810 may include a data repository 812, one or morecomputing devices 814, and, in some cases, at least one user interface816. In some cases, the data repository 812 may store information aboutone or more portfolios 822 including a plurality of exchange tradedderivatives, where the portfolios 822 may include information (e.g.,positions) about two or more different exchange traded derivatives(e.g., position 1, position 2, position n, etc.). For example, theexchange traded derivatives information may include the name of thecontract, quantity, value/price, and action (buy vs. sell) for each ofthe plurality of different positions of the portfolios 822. In somecases, the portfolios 822 may be associated with the financialinstitution, and/or one or more different customers of the financialinstitution. For example, a financial entity and/or a customer of thefinancial entity may desire to enter into one or more different exchangetraded derivatives to hedge financial risk associated with an energyproduct. In some cases, a computing device 815 and/or the user interface816 may be used to facilitate user access to the one or more of theportfolios 822. For example, a user may log into the financialinstitution computing system 810 via one or more user interface screensaccessible via the user interface 816. In some cases, the user interface816 is at a geographical location local to the financial institutioncomputer system 810 and/or at a geographical location of the user. Eachof the positions may be represented as a data element in a data filestoring information about the portfolio.

In some cases, the clearinghouse computer system 840 may include one ormore of a data repository 842, a computer device 844 and/or a userinterface 846. The clearinghouse computer system 840 may becommunicatively coupled to at least one financial institution computersystem, such as the financial institution computing system 810 via thenetwork 805. In some cases, the clearinghouse computer system 840 may beconfigured to obtain information about one or more of the portfolios822, process the information to compress the data files associated withthe portfolios 822 to reduce one or more line items associated with theportfolios 822 and/or to reduce a gross notional value associated withthe portfolios 822 to reduce a total capital charge incurred by thefinancial institution in relation to the portfolios 822 and communicateinformation about the compressed data files to the financial institutioncomputing system 810.

FIG. 9 illustrates an example flowchart 900 for reducing data elementsin a data file, according to an embodiment of the present disclosure.Embodiments may involve all, more or fewer actions than the illustratedactions. The actions may be performed in the order or sequence shown, orin a different sequence. The actions may be performed simultaneously, orin a parallel or overlapping fashion. The method may be performed byprocessing logic that may comprise hardware (circuitry, dedicated logic,etc.), software, or a combination of both. In one example, the method isperformed by the computer system 100 of FIG. 1, while in some otherexamples, some or all of the method may be performed by another machine.

Method 900 includes receiving 902, by a processor, a data file includingone or more primary data elements. The processor stores 904 the datafile in a memory coupled to the processor. The processor generates 906,from at least one of the one or more primary data elements, a pluralityof supplemental data elements. The processor determines 908 whether anyof the plurality of supplemental data elements and any of the primarydata elements offset each other. Upon determining that at least one ofthe plurality of supplemental data elements and at least one of theprimary data elements offset each other, the processor deletes 910, fromthe data file, at least one of the offset supplemental data elements orprimary data elements.

Data elements that are part of a data file received by the optimizationsystem may be referred to as primary data elements. Data elements thatare generated by the optimization system may be referred to assupplemental data elements. For example, the data file may be aportfolio of exchange traded derivatives. The data elements may be lineitems, or positions in the portfolio data file. The data elements mayinclude primary data elements that include at least one spread financialinstrument, which can be expanded/devolved into underlying leg financialinstruments. The underlying leg financial instruments generated by theoptimization system processor may be referred to as supplemental dataelements. The optimization system then offsets at least one primary dataelement (e.g., a financial instrument existing in the receivedportfolio) with at least one of the supplement data elements (e.g., afinancial instrument position generated by the optimization system).

A data element that represents a spread financial instrument may beassociated with two data elements. For example, referring to FIG. 6A,the optimizer 500 is configured to detect that position/data element 608in portfolio 602 is actually for a spread financial instrumentassociated with two other financial instruments, and that those twoother financial instruments are also represented by other data elementsin the same portfolio 602.

Data elements may be associated with a financial instrument and atransaction type, and data elements offset each other when they areassociated with the same financial instrument and opposing transactiontypes. Data elements may also be associated with a quantity, and if twodata elements offset each other (e.g., they are associated with the samefinancial instrument and opposing transaction types), and in addition,are associated with the same quantity, the optimizer removes both dataelements from the data file. If two data elements offset each other(e.g., they are associated with the same financial instrument andopposing transaction types), but are associated with differentquantities, the optimizer removes the data element with the lesserquantity from the data file.

In one embodiment, a computer implemented method for optimizing thememory associated with storing a data file includes receiving, by aprocessor, a data file including a first data element and a second dataelement; generating, from the first data element, at least a third andfourth data element; upon determining that one of the third or fourthdata elements offsets the second data element, deleting, from the datafile, the one of the third or fourth data elements and the second dataelement.

XIII. Conclusion

The illustrations of the embodiments described herein are intended toprovide a general understanding of the structure of the variousembodiments. The illustrations are not intended to serve as a completedescription of all of the elements and features of apparatus and systemsthat utilize the structures or methods described herein. It should beappreciated that wherever practicable, similar or like reference numbersmay be used in the figures and may indicate similar or likefunctionality. Many other embodiments may be apparent to those of skillin the art upon reviewing the disclosure. Other embodiments may beutilized and derived from the disclosure, such that structural andlogical substitutions and changes may be made without departing from thescope of the disclosure. Additionally, the illustrations are merelyrepresentational and may not be drawn to scale. Certain proportionswithin the illustrations may be exaggerated, while other proportions maybe minimized. Accordingly, the disclosure and the figures are to beregarded as illustrative rather than restrictive.

While this specification contains many specifics, these should not beconstrued as limitations on the scope of the invention or of what may beclaimed, but rather as descriptions of features specific to particularembodiments of the invention. Certain features that are described inthis specification in the context of separate embodiments can also beimplemented in combination in a single embodiment. Conversely, variousfeatures that are described in the context of a single embodiment canalso be implemented in multiple embodiments separately or in anysuitable sub-combination. Moreover, although features may be describedas acting in certain combinations and even initially claimed as such,one or more features from a claimed combination can in some cases beexcised from the combination, and the claimed combination may bedirected to a sub-combination or variation of a sub-combination.

Similarly, while operations are depicted in the drawings and describedherein in a particular order, this should not be understood as requiringthat such operations be performed in the particular order shown or insequential order, or that all illustrated operations be performed, toachieve desirable results. In certain circumstances, multitasking andparallel processing may be advantageous. Moreover, the separation ofvarious system components in the described embodiments should not beunderstood as requiring such separation in all embodiments, and itshould be understood that the described program components and systemscan generally be integrated together in a single software product orpackaged into multiple software products.

One or more embodiments of the disclosure may be referred to herein,individually and/or collectively, by the term “invention” merely forconvenience and without intending to voluntarily limit the scope of thisapplication to any particular invention or inventive concept. Moreover,although specific embodiments have been illustrated and describedherein, it should be appreciated that any subsequent arrangementdesigned to achieve the same or similar purpose may be substituted forthe specific embodiments shown. This disclosure is intended to cover anyand all subsequent adaptations or variations of various embodiments.Combinations of the above embodiments, and other embodiments notspecifically described herein, will be apparent to those of skill in theart upon reviewing the description.

The Abstract of the Disclosure is provided to comply with 37 C.F.R. §1.72(b) and is submitted with the understanding that it will not be usedto interpret or limit the scope or meaning of the claims. In addition,in the foregoing Detailed Description, various features may be groupedtogether or described in a single embodiment for the purpose ofstreamlining the disclosure. This disclosure is not to be interpreted asreflecting an intention that the claimed embodiments require morefeatures than are expressly recited in each claim. Rather, as thefollowing claims reflect, inventive subject matter may be directed toless than all of the features of any of the disclosed embodiments. Thus,the following claims are incorporated into the Detailed Description,with each claim standing on its own as defining separately claimedsubject matter.

It is therefore intended that the foregoing detailed description beregarded as illustrative rather than limiting, and that it be understoodthat it is the following claims, including all equivalents, that areintended to define the spirit and scope of this invention.

The invention claimed is:
 1. A computer system for compressing a datafile, the computer system comprising: a processor; and a non-transitorycomputer readable medium storing processor-issuable instructions that,when executed by the processor, cause the processor to: receive a datafile including one or more primary data elements; store the data file ina memory coupled to the processor; generate, from at least one of theone or more primary data elements, a plurality of supplemental dataelements; determine whether any of the plurality of supplemental dataelements and any of the primary data elements offset each other; andupon determining that at least one of the plurality of supplemental dataelements and at least one of the primary data elements offset eachother, delete, from the data file, at least one of the offsetsupplemental data elements or primary data elements.
 2. The computersystem of claim 1, wherein each data element is associated with afinancial instrument and a transaction type, and wherein data elementsoffset each other when they are associated with the same financialinstrument and opposing transaction types.
 3. The computer implementedmethod of claim 2, wherein a transaction type may be one of acquire afinancial instrument or relinquish a financial instrument.
 4. Thecomputer system of claim 1, wherein the size of the data file after atleast one of the offset supplemental data elements or primary dataelements is deleted is smaller than the size of the data file before theplurality of supplemental data elements is generated.
 5. The computersystem of claim 4, wherein the size of the data file after the pluralityof supplemental data elements is generated is larger than the size ofthe data file before the plurality of supplemental data elements isgenerated.
 6. The computer system of claim 1, wherein the computersystem is a first computer system, and wherein the instructions arefurther configured to cause the processor to, after at least one of theoffset supplemental data elements or primary data elements is deleted,automatically transmit the data file to a second computer system over anetwork.
 7. The computer system of claim 1, wherein the data file isassociated with a derivatives portfolio of a market participant.
 8. Thecomputer system of claim 7, wherein an offset primary data elementcomprises a derivatives spread financial instrument, and supplementaldata elements offsetting a primary data element comprise leg financialinstruments underlying the derivatives spread financial instrument. 9.The computer system of claim 7, wherein the instructions are furtherconfigured to cause the processor to, after at least one of the offsetsupplemental data elements or primary data elements is deleted,automatically calculate a capital requirement for the derivativesportfolio.
 10. The computer system of claim 1, wherein the instructionsare further configured to cause the processor to: after receiving thedata file, parse the data file to identify primary data elements thatare associated with at least two data elements, wherein generating theplurality of supplemental data elements comprises expanding eachidentified primary data element into the at least two associated dataelements.
 11. A computer implemented method of reducing data elements ina data file, the method comprising: receiving, by a processor, a datafile including one or more primary data elements; storing, by theprocessor, the data file in a memory coupled to the processor;generating, by the processor, from at least one of the one or moreprimary data elements, a plurality of supplemental data elements;determining, by the processor, whether any of the plurality ofsupplemental data elements and any of the primary data elements offseteach other; and upon determining that at least one of the plurality ofsupplemental data elements and at least one of the primary data elementsoffset each other, deleting, by the processor, from the data file, atleast one of the offset supplemental data elements or primary dataelements.
 12. The computer implemented method of claim 11, wherein eachdata element is associated with a financial instrument and a transactiontype, and wherein data elements offset each other when they areassociated with the same financial instrument and opposing transactiontypes.
 13. The computer implemented method of claim 12, wherein atransaction type may be one of acquire a financial instrument orrelinquish a financial instrument.
 14. The computer implemented methodof claim 11, wherein the size of the data file after the deleting stepis smaller than the size of the data file before the generating step.15. The computer implemented method of claim 14, wherein the size of thedata file after the generating step is larger than the size of the datafile before the generating step.
 16. The computer implemented method ofclaim 11, further comprising, after the deleting step, automaticallytransmitting, by the processor, the data file to a user computer systemover a network.
 17. The computer implemented method of claim 11, whereinthe data file is associated with a derivatives portfolio of a marketparticipant.
 18. The computer implemented method of claim 17, wherein anoffset primary data element comprises a derivatives spread financialinstrument, and supplemental data elements offsetting a primary dataelement comprise leg financial instruments underlying the derivativesspread financial instrument.
 19. The computer implemented method ofclaim 17, further comprising, after the deleting step, automaticallycalculating, by the processor, a capital requirement for the derivativesportfolio.
 20. The computer implemented method of claim 11, furthercomprising: after receiving the data file, parsing, by the processor,the data file to identify primary data elements that are associated withat least two data elements, wherein generating the plurality ofsupplemental data elements comprises expanding each identified primarydata element into the at least two associated data elements.
 21. A datafile optimization system comprising: a processor; and a non-transitorycomputer readable medium storing processor-issuable instructions that,when executed by the processor, cause the processor to: receive a firstdata file including a plurality of data elements including first andsecond data elements; generate, based on the first data file, a seconddata file including the first and second data elements and third andfourth data elements; determine that one of the third or fourth dateelements offsets the second data element; and generate a third data fileincluding the first data element and the other of the third or fourthdata elements.
 22. The data file optimization system of claim 21,wherein the second data file is larger than the first data file, and thethird data file is smaller than the first data file.
 23. A computersystem comprising: means for receiving a data file including one or moreprimary data elements; means for storing the data file; means forgenerating, from at least one of the one or more primary data elements,a plurality of supplemental data elements; means for determining whetherany of the plurality of supplemental data elements and any of theprimary data elements offset each other; and means for, upon determiningthat at least one of the plurality of supplemental data elements and atleast one of the primary data elements offset each other, deleting, fromthe data file, at least one of the offset supplemental data elements orprimary data elements.